NVIDIA Technical Blog This NVIDIA tutorial adapts a Cache-Aware FastConformer-RNNT multilingual streaming ASR model to Najdi and Hijazi Saudi dialects using minimal curation of SADA 2022 (retaining 103,559 of 125,490 utterances, 133.7 hours, 82.5%), a weighted replay mix of 90% Saudi speech with 7% English and 3% Arabic FLEURS, and duration bucketing, training for 12,000 steps in about 4.5 hours on two GPUs, which lowers Najdi+Hijazi test WER from 55.05% to 29.96% and CER from 31.63% to 12.18%, full SADA WER from 58.84% to 35.61%, while FLEURS English WER falls from 11.04% to 10.42% and Arabic WER from 12.67% to 11.41%; it also compares encoder unfreezing depths (top 6 at 33.42%, top 8 at 32.32%, all 24 layers at 29.96%) and inference-time settings ([56,13] attention context gains 1.
This NVIDIA tutorial adapts a Cache-Aware FastConformer-RNNT multilingual streaming ASR model to Najdi and Hijazi Saudi dialects using minimal curation of SADA 2022 (retaining 103,559 of 125,490 utterances, 133.7 hours, 82.5%), a weighted replay mix of 90% Saudi speech with 7% English and 3% Arabic FLEURS, and duration bucketing, training for 12,000 steps in about 4.5 hours on two GPUs, which lowers Najdi+Hijazi test WER from 55.05% to 29.96% and CER from 31.63% to 12.18%, full SADA WER from 58.84% to 35.61%, while FLEURS English WER falls from 11.04% to 10.42% and Arabic WER from 12.67% to 11.41%; it also compares encoder unfreezing depths (top 6 at 33.42%, top 8 at 32.32%, all 24 layers at 29.96%) and inference-time settings ([56,13] attention context gains 1.
This NVIDIA tutorial adapts a Cache-Aware FastConformer-RNNT multilingual streaming ASR model to Najdi and Hijazi Saudi dialects using minimal curation of SADA 2022 (retaining 103,559 of 125,490 utterances, 133.7 hours, 82.5%), a weighted replay mix of 90% Saudi speech with 7% English and 3% Arabic FLEURS, and duration bucketing, training for 12,000 steps in about 4.5 hours on two GPUs, which lowers Najdi+Hijazi test WER from 55.05% to 29.96% and CER from 31.63% to 12.18%, full SADA WER from 58.84% to 35.61%, while FLEURS English WER falls from 11.04% to 10.42% and Arabic WER from 12.67% to 11.41%; it also compares encoder unfreezing depths (top 6 at 33.42%, top 8 at 32.32%, all 24 layers at 29.96%) and inference-time settings ([56,13] attention context gains 1.
This NVIDIA tutorial adapts a Cache-Aware FastConformer-RNNT multilingual streaming ASR model to Najdi and Hijazi Saudi dialects using minimal curation of SADA 2022 (retaining 103,559 of 125,490 utterances, 133.7 hours, 82.5%), a weighted replay mix of 90% Saudi speech with 7% English and 3% Arabic FLEURS, and duration bucketing, training for 12,000 steps in about 4.5 hours on two GPUs, which lowers Najdi+Hijazi test WER from 55.05% to 29.96% and CER from 31.63% to 12.18%, full SADA WER from 58.84% to 35.61%, while FLEURS English WER falls from 11.04% to 10.42% and Arabic WER from 12.67% to 11.41%; it also compares encoder unfreezing depths (top 6 at 33.42%, top 8 at 32.32%, all 24 layers at 29.96%) and inference-time settings ([56,13] attention context gains 1.
British Journal of Radiology This review synthesizes evidence on opportunistically identifying and quantifying coronary artery calcium (CAC) on thoracic CT performed for other clinical indications (routine thoracic CT, lung cancer screening CT, attenuation correction CT), reporting a pooled CAC prevalence of 52%, independent associations with all-cause mortality (pooled relative risk 2.13) and major adverse cardiovascular events (pooled relative risk 2.61), and reviewing novel applications including AI/machine learning automated scoring, radiomics, photon-counting CT, and CAC as a multi-system biomarker, while noting that no randomized trials assessing the clinical impact of this approach have yet been published.
This review synthesizes evidence on opportunistically identifying and quantifying coronary artery calcium (CAC) on thoracic CT performed for other clinical indications (routine thoracic CT, lung cancer screening CT, attenuation correction CT), reporting a pooled CAC prevalence of 52%, independent associations with all-cause mortality (pooled relative risk 2.13) and major adverse cardiovascular events (pooled relative risk 2.61), and reviewing novel applications including AI/machine learning automated scoring, radiomics, photon-counting CT, and CAC as a multi-system biomarker, while noting that no randomized trials assessing the clinical impact of this approach have yet been published.
This review synthesizes evidence on opportunistically identifying and quantifying coronary artery calcium (CAC) on thoracic CT performed for other clinical indications (routine thoracic CT, lung cancer screening CT, attenuation correction CT), reporting a pooled CAC prevalence of 52%, independent associations with all-cause mortality (pooled relative risk 2.13) and major adverse cardiovascular events (pooled relative risk 2.61), and reviewing novel applications including AI/machine learning automated scoring, radiomics, photon-counting CT, and CAC as a multi-system biomarker, while noting that no randomized trials assessing the clinical impact of this approach have yet been published.
This review synthesizes evidence on opportunistically identifying and quantifying coronary artery calcium (CAC) on thoracic CT performed for other clinical indications (routine thoracic CT, lung cancer screening CT, attenuation correction CT), reporting a pooled CAC prevalence of 52%, independent associations with all-cause mortality (pooled relative risk 2.13) and major adverse cardiovascular events (pooled relative risk 2.61), and reviewing novel applications including AI/machine learning automated scoring, radiomics, photon-counting CT, and CAC as a multi-system biomarker, while noting that no randomized trials assessing the clinical impact of this approach have yet been published.
British Journal of Radiology This review systematically examines the anatomy, physiology, and pathophysiological roles of epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT), compares CT, MRI, and echocardiography for quantifying these depots, notes that deep-learning segmentation (with Dice coefficients reported from 0.82 to 0.98) improves accuracy and reproducibility, and summarizes conflicting imaging evidence on EAT's link to cardiovascular outcomes alongside findings that statins, GLP-1 receptor agonists, SGLT2 inhibitors, and lifestyle interventions can reduce EAT volume.
This review systematically examines the anatomy, physiology, and pathophysiological roles of epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT), compares CT, MRI, and echocardiography for quantifying these depots, notes that deep-learning segmentation (with Dice coefficients reported from 0.82 to 0.98) improves accuracy and reproducibility, and summarizes conflicting imaging evidence on EAT's link to cardiovascular outcomes alongside findings that statins, GLP-1 receptor agonists, SGLT2 inhibitors, and lifestyle interventions can reduce EAT volume.
This review systematically examines the anatomy, physiology, and pathophysiological roles of epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT), compares CT, MRI, and echocardiography for quantifying these depots, notes that deep-learning segmentation (with Dice coefficients reported from 0.82 to 0.98) improves accuracy and reproducibility, and summarizes conflicting imaging evidence on EAT's link to cardiovascular outcomes alongside findings that statins, GLP-1 receptor agonists, SGLT2 inhibitors, and lifestyle interventions can reduce EAT volume.
This review systematically examines the anatomy, physiology, and pathophysiological roles of epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT), compares CT, MRI, and echocardiography for quantifying these depots, notes that deep-learning segmentation (with Dice coefficients reported from 0.82 to 0.98) improves accuracy and reproducibility, and summarizes conflicting imaging evidence on EAT's link to cardiovascular outcomes alongside findings that statins, GLP-1 receptor agonists, SGLT2 inhibitors, and lifestyle interventions can reduce EAT volume.
Pakistan Journal of Pharmaceutical Sciences This retrospective study analyzed patients undergoing inguinal hernia repair between January 2021 and December 2024, using 1:1 nearest-neighbor propensity score matching to compare 280 patients who received perioperative celecoxib plus dexamethasone with 280 who did not, and found an overall one-year recurrence rate of 5.0% (28/560), an independent association between treatment and lower recurrence risk (HR=0.45, 95% CI: 0.24-0.84, P=0.011), a significant interaction with BMI (P=0.032) with a stronger association in obese patients (HR=0.32, 95% CI: 0.14-0.71) than non-obese patients (HR=0.68, 95% CI: 0.31-1.52), along with lower acute pain scores, less postoperative nausea and vomiting (P<0.001), lower chronic pain risk (aOR=0.42, 95% CI: 0.23-0.78, P=0.
This retrospective study analyzed patients undergoing inguinal hernia repair between January 2021 and December 2024, using 1:1 nearest-neighbor propensity score matching to compare 280 patients who received perioperative celecoxib plus dexamethasone with 280 who did not, and found an overall one-year recurrence rate of 5.0% (28/560), an independent association between treatment and lower recurrence risk (HR=0.45, 95% CI: 0.24-0.84, P=0.011), a significant interaction with BMI (P=0.032) with a stronger association in obese patients (HR=0.32, 95% CI: 0.14-0.71) than non-obese patients (HR=0.68, 95% CI: 0.31-1.52), along with lower acute pain scores, less postoperative nausea and vomiting (P<0.001), lower chronic pain risk (aOR=0.42, 95% CI: 0.23-0.78, P=0.
This retrospective study analyzed patients undergoing inguinal hernia repair between January 2021 and December 2024, using 1:1 nearest-neighbor propensity score matching to compare 280 patients who received perioperative celecoxib plus dexamethasone with 280 who did not, and found an overall one-year recurrence rate of 5.0% (28/560), an independent association between treatment and lower recurrence risk (HR=0.45, 95% CI: 0.24-0.84, P=0.011), a significant interaction with BMI (P=0.032) with a stronger association in obese patients (HR=0.32, 95% CI: 0.14-0.71) than non-obese patients (HR=0.68, 95% CI: 0.31-1.52), along with lower acute pain scores, less postoperative nausea and vomiting (P<0.001), lower chronic pain risk (aOR=0.42, 95% CI: 0.23-0.78, P=0.
This retrospective study analyzed patients undergoing inguinal hernia repair between January 2021 and December 2024, using 1:1 nearest-neighbor propensity score matching to compare 280 patients who received perioperative celecoxib plus dexamethasone with 280 who did not, and found an overall one-year recurrence rate of 5.0% (28/560), an independent association between treatment and lower recurrence risk (HR=0.45, 95% CI: 0.24-0.84, P=0.011), a significant interaction with BMI (P=0.032) with a stronger association in obese patients (HR=0.32, 95% CI: 0.14-0.71) than non-obese patients (HR=0.68, 95% CI: 0.31-1.52), along with lower acute pain scores, less postoperative nausea and vomiting (P<0.001), lower chronic pain risk (aOR=0.42, 95% CI: 0.23-0.78, P=0.
University of Twente Research Information Using the Multimodal Activity Sensing Dataset (MASD; 27 activities, 20 participants), the study tests whether ambient WiFi Channel State Information (CSI) can substitute for a body-worn inertial measurement unit (IMU) in human activity recognition; the authors find that the dataset's released machine-learning-ready files expose a degraded signed CSI representation rather than the documented amplitude, so they rebuild amplitude and antenna-ratio Doppler from the raw complex CSI, recover omitted participant identifiers, and re-evaluate subject-independently under a controlled multi-seed protocol, finding WiFi systematically weak: every backbone they try reaches only 6-11% weighted accuracy on the 27-class set against 73-80% for IMU, with usable accuracy on 0 of 27 activities; the corrected r
Using the Multimodal Activity Sensing Dataset (MASD; 27 activities, 20 participants), the study tests whether ambient WiFi Channel State Information (CSI) can substitute for a body-worn inertial measurement unit (IMU) in human activity recognition; the authors find that the dataset's released machine-learning-ready files expose a degraded signed CSI representation rather than the documented amplitude, so they rebuild amplitude and antenna-ratio Doppler from the raw complex CSI, recover omitted participant identifiers, and re-evaluate subject-independently under a controlled multi-seed protocol, finding WiFi systematically weak: every backbone they try reaches only 6-11% weighted accuracy on the 27-class set against 73-80% for IMU, with usable accuracy on 0 of 27 activities; the corrected r
Using the Multimodal Activity Sensing Dataset (MASD; 27 activities, 20 participants), the study tests whether ambient WiFi Channel State Information (CSI) can substitute for a body-worn inertial measurement unit (IMU) in human activity recognition; the authors find that the dataset's released machine-learning-ready files expose a degraded signed CSI representation rather than the documented amplitude, so they rebuild amplitude and antenna-ratio Doppler from the raw complex CSI, recover omitted participant identifiers, and re-evaluate subject-independently under a controlled multi-seed protocol, finding WiFi systematically weak: every backbone they try reaches only 6-11% weighted accuracy on the 27-class set against 73-80% for IMU, with usable accuracy on 0 of 27 activities; the corrected r
Using the Multimodal Activity Sensing Dataset (MASD; 27 activities, 20 participants), the study tests whether ambient WiFi Channel State Information (CSI) can substitute for a body-worn inertial measurement unit (IMU) in human activity recognition; the authors find that the dataset's released machine-learning-ready files expose a degraded signed CSI representation rather than the documented amplitude, so they rebuild amplitude and antenna-ratio Doppler from the raw complex CSI, recover omitted participant identifiers, and re-evaluate subject-independently under a controlled multi-seed protocol, finding WiFi systematically weak: every backbone they try reaches only 6-11% weighted accuracy on the 27-class set against 73-80% for IMU, with usable accuracy on 0 of 27 activities; the corrected r
Urogynecology In this cross-sectional study, six urogynecologists developed six questions comparing two treatment options for common urogynecological conditions and entered them into ChatGPT to create decision aid tools; patients and physicians then rated understandability with a Patient Education Materials Assessment Tool, physicians rated reliability with a modified DISCERN instrument and accuracy on a 5-point Likert scale, and readability was assessed with the Flesch-Kincaid Reading Ease score, showing high patient and physician understandability for all tools, fair reliability with an average mDISCERN score of 26, accuracy below 4 (unfavorable) on 2 of the tools, and a high reading level required overall.
In this cross-sectional study, six urogynecologists developed six questions comparing two treatment options for common urogynecological conditions and entered them into ChatGPT to create decision aid tools; patients and physicians then rated understandability with a Patient Education Materials Assessment Tool, physicians rated reliability with a modified DISCERN instrument and accuracy on a 5-point Likert scale, and readability was assessed with the Flesch-Kincaid Reading Ease score, showing high patient and physician understandability for all tools, fair reliability with an average mDISCERN score of 26, accuracy below 4 (unfavorable) on 2 of the tools, and a high reading level required overall.
In this cross-sectional study, six urogynecologists developed six questions comparing two treatment options for common urogynecological conditions and entered them into ChatGPT to create decision aid tools; patients and physicians then rated understandability with a Patient Education Materials Assessment Tool, physicians rated reliability with a modified DISCERN instrument and accuracy on a 5-point Likert scale, and readability was assessed with the Flesch-Kincaid Reading Ease score, showing high patient and physician understandability for all tools, fair reliability with an average mDISCERN score of 26, accuracy below 4 (unfavorable) on 2 of the tools, and a high reading level required overall.
In this cross-sectional study, six urogynecologists developed six questions comparing two treatment options for common urogynecological conditions and entered them into ChatGPT to create decision aid tools; patients and physicians then rated understandability with a Patient Education Materials Assessment Tool, physicians rated reliability with a modified DISCERN instrument and accuracy on a 5-point Likert scale, and readability was assessed with the Flesch-Kincaid Reading Ease score, showing high patient and physician understandability for all tools, fair reliability with an average mDISCERN score of 26, accuracy below 4 (unfavorable) on 2 of the tools, and a high reading level required overall.
Journal of Cataract & Refractive Surgery This two-center clinical validation study recruited 127 individuals with different severities of nuclear cataract from Thailand (n = 81) and Shenzhen, China (n = 46), imaged them with AS-OCT and graded images under the LOCS III standard, developed automated machine learning models to extract nuclear region annotation and analyzed feature-based quantifiers, finding that pixel-based features such as mean, variance, root mean square, interquartile range, and percentiles significantly correlate with NC grading (P < .01), that variance, standard deviation, and median showed high consistency while kurtosis and skewness were negatively correlated, and that the prediction model achieved 0.81 accuracy at the SZRM center (F1 0.82) and 0.87 at the Thai center (F1 0.
This two-center clinical validation study recruited 127 individuals with different severities of nuclear cataract from Thailand (n = 81) and Shenzhen, China (n = 46), imaged them with AS-OCT and graded images under the LOCS III standard, developed automated machine learning models to extract nuclear region annotation and analyzed feature-based quantifiers, finding that pixel-based features such as mean, variance, root mean square, interquartile range, and percentiles significantly correlate with NC grading (P < .01), that variance, standard deviation, and median showed high consistency while kurtosis and skewness were negatively correlated, and that the prediction model achieved 0.81 accuracy at the SZRM center (F1 0.82) and 0.87 at the Thai center (F1 0.
This two-center clinical validation study recruited 127 individuals with different severities of nuclear cataract from Thailand (n = 81) and Shenzhen, China (n = 46), imaged them with AS-OCT and graded images under the LOCS III standard, developed automated machine learning models to extract nuclear region annotation and analyzed feature-based quantifiers, finding that pixel-based features such as mean, variance, root mean square, interquartile range, and percentiles significantly correlate with NC grading (P < .01), that variance, standard deviation, and median showed high consistency while kurtosis and skewness were negatively correlated, and that the prediction model achieved 0.81 accuracy at the SZRM center (F1 0.82) and 0.87 at the Thai center (F1 0.
This two-center clinical validation study recruited 127 individuals with different severities of nuclear cataract from Thailand (n = 81) and Shenzhen, China (n = 46), imaged them with AS-OCT and graded images under the LOCS III standard, developed automated machine learning models to extract nuclear region annotation and analyzed feature-based quantifiers, finding that pixel-based features such as mean, variance, root mean square, interquartile range, and percentiles significantly correlate with NC grading (P < .01), that variance, standard deviation, and median showed high consistency while kurtosis and skewness were negatively correlated, and that the prediction model achieved 0.81 accuracy at the SZRM center (F1 0.82) and 0.87 at the Thai center (F1 0.
Journal of Nursing Research Using a qualitative descriptive design with focus group interviews conducted in South Korea between February and August 2024, this study interviewed 10 nursing applicants with prior AI-based competency assessment (AICA) experience and 10 nurse educators (professors and nurse managers), and through conventional content analysis derived eight subthemes and four themes from 32 codes, finding that participants recognized AICA's efficiency and objectivity for large-scale recruitment while questioning opaque evaluation criteria, misalignment with person-centered nursing values, and fairness risks from network, lighting, device, and information-support gaps, and recommending nurse-specific algorithms, clear criteria, and positioning AI as a support to face-to-face interviews.
Using a qualitative descriptive design with focus group interviews conducted in South Korea between February and August 2024, this study interviewed 10 nursing applicants with prior AI-based competency assessment (AICA) experience and 10 nurse educators (professors and nurse managers), and through conventional content analysis derived eight subthemes and four themes from 32 codes, finding that participants recognized AICA's efficiency and objectivity for large-scale recruitment while questioning opaque evaluation criteria, misalignment with person-centered nursing values, and fairness risks from network, lighting, device, and information-support gaps, and recommending nurse-specific algorithms, clear criteria, and positioning AI as a support to face-to-face interviews.
Using a qualitative descriptive design with focus group interviews conducted in South Korea between February and August 2024, this study interviewed 10 nursing applicants with prior AI-based competency assessment (AICA) experience and 10 nurse educators (professors and nurse managers), and through conventional content analysis derived eight subthemes and four themes from 32 codes, finding that participants recognized AICA's efficiency and objectivity for large-scale recruitment while questioning opaque evaluation criteria, misalignment with person-centered nursing values, and fairness risks from network, lighting, device, and information-support gaps, and recommending nurse-specific algorithms, clear criteria, and positioning AI as a support to face-to-face interviews.
Using a qualitative descriptive design with focus group interviews conducted in South Korea between February and August 2024, this study interviewed 10 nursing applicants with prior AI-based competency assessment (AICA) experience and 10 nurse educators (professors and nurse managers), and through conventional content analysis derived eight subthemes and four themes from 32 codes, finding that participants recognized AICA's efficiency and objectivity for large-scale recruitment while questioning opaque evaluation criteria, misalignment with person-centered nursing values, and fairness risks from network, lighting, device, and information-support gaps, and recommending nurse-specific algorithms, clear criteria, and positioning AI as a support to face-to-face interviews.
DOAJ (DOAJ: Directory of Open Access Journals) This study applies scientometric analysis to literature on intelligent knowledge management in water treatment, organizing the analysis around thematic trends, collaboration networks, research gaps, and future research priorities, drawing on references that span AI-based groundwater quality assessment, machine-learning water quality index prediction, knowledge-graph management of industrial water treatment knowledge, and multiple bibliometric reviews of water and wastewater treatment.
This study applies scientometric analysis to literature on intelligent knowledge management in water treatment, organizing the analysis around thematic trends, collaboration networks, research gaps, and future research priorities, drawing on references that span AI-based groundwater quality assessment, machine-learning water quality index prediction, knowledge-graph management of industrial water treatment knowledge, and multiple bibliometric reviews of water and wastewater treatment.
This study applies scientometric analysis to literature on intelligent knowledge management in water treatment, organizing the analysis around thematic trends, collaboration networks, research gaps, and future research priorities, drawing on references that span AI-based groundwater quality assessment, machine-learning water quality index prediction, knowledge-graph management of industrial water treatment knowledge, and multiple bibliometric reviews of water and wastewater treatment.
This study applies scientometric analysis to literature on intelligent knowledge management in water treatment, organizing the analysis around thematic trends, collaboration networks, research gaps, and future research priorities, drawing on references that span AI-based groundwater quality assessment, machine-learning water quality index prediction, knowledge-graph management of industrial water treatment knowledge, and multiple bibliometric reviews of water and wastewater treatment.
DOAJ (DOAJ: Directory of Open Access Journals) Titled "Scientometric Analysis of Research Trends in Smart and Sustainable Architecture in Educational Environments: With an Emphasis on Green Schools and Campuses," the work is, as far as the loaded text shows, a scientometric/bibliometric analysis that gathers and cites literature on smart and sustainable architecture in educational environments, green schools and campuses, spanning green school assessment, sustainable education space design, smart buildings and smart campuses, BIM and IoT, biophilic design, energy efficiency, and net-zero energy buildings, and it cites scientometric and visualization tools such as Bibliometrix, VOSviewer, and CiteSpace along with methodological sources on co-citation and science mapping; however, the loaded text presents only a reference list and contai
Titled "Scientometric Analysis of Research Trends in Smart and Sustainable Architecture in Educational Environments: With an Emphasis on Green Schools and Campuses," the work is, as far as the loaded text shows, a scientometric/bibliometric analysis that gathers and cites literature on smart and sustainable architecture in educational environments, green schools and campuses, spanning green school assessment, sustainable education space design, smart buildings and smart campuses, BIM and IoT, biophilic design, energy efficiency, and net-zero energy buildings, and it cites scientometric and visualization tools such as Bibliometrix, VOSviewer, and CiteSpace along with methodological sources on co-citation and science mapping; however, the loaded text presents only a reference list and contai
Titled "Scientometric Analysis of Research Trends in Smart and Sustainable Architecture in Educational Environments: With an Emphasis on Green Schools and Campuses," the work is, as far as the loaded text shows, a scientometric/bibliometric analysis that gathers and cites literature on smart and sustainable architecture in educational environments, green schools and campuses, spanning green school assessment, sustainable education space design, smart buildings and smart campuses, BIM and IoT, biophilic design, energy efficiency, and net-zero energy buildings, and it cites scientometric and visualization tools such as Bibliometrix, VOSviewer, and CiteSpace along with methodological sources on co-citation and science mapping; however, the loaded text presents only a reference list and contai
Titled "Scientometric Analysis of Research Trends in Smart and Sustainable Architecture in Educational Environments: With an Emphasis on Green Schools and Campuses," the work is, as far as the loaded text shows, a scientometric/bibliometric analysis that gathers and cites literature on smart and sustainable architecture in educational environments, green schools and campuses, spanning green school assessment, sustainable education space design, smart buildings and smart campuses, BIM and IoT, biophilic design, energy efficiency, and net-zero energy buildings, and it cites scientometric and visualization tools such as Bibliometrix, VOSviewer, and CiteSpace along with methodological sources on co-citation and science mapping; however, the loaded text presents only a reference list and contai
DOAJ (DOAJ: Directory of Open Access Journals) Using a convenience sample of 100 scientometric experts, data analysts, university research-evaluation unit experts and managers, and representatives of scientific databases, reference libraries, and scientometric service companies in Tehran, the study collected data with a researcher-designed Likert-scale questionnaire based on English-language articles and tested hypotheses with simple regression in SPSS 26, finding that the use of new technologies in the scientometric process is positively associated with increased accuracy in scientific evaluation (the coefficient of determination shows 73% of the variance in accuracy explained by new-technology use), that technological innovation within scientometric frameworks promotes fairness (64% of variance in fairness explained), that new-techno
Using a convenience sample of 100 scientometric experts, data analysts, university research-evaluation unit experts and managers, and representatives of scientific databases, reference libraries, and scientometric service companies in Tehran, the study collected data with a researcher-designed Likert-scale questionnaire based on English-language articles and tested hypotheses with simple regression in SPSS 26, finding that the use of new technologies in the scientometric process is positively associated with increased accuracy in scientific evaluation (the coefficient of determination shows 73% of the variance in accuracy explained by new-technology use), that technological innovation within scientometric frameworks promotes fairness (64% of variance in fairness explained), that new-techno
Using a convenience sample of 100 scientometric experts, data analysts, university research-evaluation unit experts and managers, and representatives of scientific databases, reference libraries, and scientometric service companies in Tehran, the study collected data with a researcher-designed Likert-scale questionnaire based on English-language articles and tested hypotheses with simple regression in SPSS 26, finding that the use of new technologies in the scientometric process is positively associated with increased accuracy in scientific evaluation (the coefficient of determination shows 73% of the variance in accuracy explained by new-technology use), that technological innovation within scientometric frameworks promotes fairness (64% of variance in fairness explained), that new-techno
Using a convenience sample of 100 scientometric experts, data analysts, university research-evaluation unit experts and managers, and representatives of scientific databases, reference libraries, and scientometric service companies in Tehran, the study collected data with a researcher-designed Likert-scale questionnaire based on English-language articles and tested hypotheses with simple regression in SPSS 26, finding that the use of new technologies in the scientometric process is positively associated with increased accuracy in scientific evaluation (the coefficient of determination shows 73% of the variance in accuracy explained by new-technology use), that technological innovation within scientometric frameworks promotes fairness (64% of variance in fairness explained), that new-techno
DOAJ (DOAJ: Directory of Open Access Journals) Using scientometric methods on 269 original research articles retained after PRISMA screening from Scopus and Web of Science, this study finds that the intellectual core of XAI research in decision dashboards is organized around explainable AI, decision making, and deep learning, that themes have shifted over time from classical machine learning such as neural networks and support vector machines toward visual deep learning, visualization techniques, trust, and intelligent decision support systems, and that the field is moving from a technology-centered toward a human- and decision-centered paradigm.
Using scientometric methods on 269 original research articles retained after PRISMA screening from Scopus and Web of Science, this study finds that the intellectual core of XAI research in decision dashboards is organized around explainable AI, decision making, and deep learning, that themes have shifted over time from classical machine learning such as neural networks and support vector machines toward visual deep learning, visualization techniques, trust, and intelligent decision support systems, and that the field is moving from a technology-centered toward a human- and decision-centered paradigm.
Using scientometric methods on 269 original research articles retained after PRISMA screening from Scopus and Web of Science, this study finds that the intellectual core of XAI research in decision dashboards is organized around explainable AI, decision making, and deep learning, that themes have shifted over time from classical machine learning such as neural networks and support vector machines toward visual deep learning, visualization techniques, trust, and intelligent decision support systems, and that the field is moving from a technology-centered toward a human- and decision-centered paradigm.
Using scientometric methods on 269 original research articles retained after PRISMA screening from Scopus and Web of Science, this study finds that the intellectual core of XAI research in decision dashboards is organized around explainable AI, decision making, and deep learning, that themes have shifted over time from classical machine learning such as neural networks and support vector machines toward visual deep learning, visualization techniques, trust, and intelligent decision support systems, and that the field is moving from a technology-centered toward a human- and decision-centered paradigm.
London School of Economics and Political Science Research Online (London School of Economics and Political Science) Using a Penrosian framework and World Bank Enterprise Surveys data on 4,254 African exporters surveyed between 2011 and 2020, the study tests whether pursuing direct and indirect exporting simultaneously yields stronger innovation than either mode alone, and finds that firms combining both modes innovate significantly more on product and process innovation, with the relationship robust across specifications and estimation techniques, while the four moderators tested only partly match theoretical predictions.
Using a Penrosian framework and World Bank Enterprise Surveys data on 4,254 African exporters surveyed between 2011 and 2020, the study tests whether pursuing direct and indirect exporting simultaneously yields stronger innovation than either mode alone, and finds that firms combining both modes innovate significantly more on product and process innovation, with the relationship robust across specifications and estimation techniques, while the four moderators tested only partly match theoretical predictions.
Using a Penrosian framework and World Bank Enterprise Surveys data on 4,254 African exporters surveyed between 2011 and 2020, the study tests whether pursuing direct and indirect exporting simultaneously yields stronger innovation than either mode alone, and finds that firms combining both modes innovate significantly more on product and process innovation, with the relationship robust across specifications and estimation techniques, while the four moderators tested only partly match theoretical predictions.
Using a Penrosian framework and World Bank Enterprise Surveys data on 4,254 African exporters surveyed between 2011 and 2020, the study tests whether pursuing direct and indirect exporting simultaneously yields stronger innovation than either mode alone, and finds that firms combining both modes innovate significantly more on product and process innovation, with the relationship robust across specifications and estimation techniques, while the four moderators tested only partly match theoretical predictions.
American Journal of Respiratory and Critical Care Medicine An international multidisciplinary working group of 41 experts systematically reviewed 922 citations up to March 17, 2025, revised the 2016 acute exacerbation (AE) definition—previously limited to idiopathic pulmonary fibrosis (IPF)—into an AE-fILD definition applicable across all fibrotic interstitial lung diseases (anchored in diffuse alveolar damage with or without organizing pneumonia), proposed the broader concept of acute respiratory worsening (ARW) to capture acute deteriorations not attributable to DAD, and summarized evidence on epidemiology, risk factors, prognosis, and management while discussing AE as a clinical trial endpoint.
An international multidisciplinary working group of 41 experts systematically reviewed 922 citations up to March 17, 2025, revised the 2016 acute exacerbation (AE) definition—previously limited to idiopathic pulmonary fibrosis (IPF)—into an AE-fILD definition applicable across all fibrotic interstitial lung diseases (anchored in diffuse alveolar damage with or without organizing pneumonia), proposed the broader concept of acute respiratory worsening (ARW) to capture acute deteriorations not attributable to DAD, and summarized evidence on epidemiology, risk factors, prognosis, and management while discussing AE as a clinical trial endpoint.
An international multidisciplinary working group of 41 experts systematically reviewed 922 citations up to March 17, 2025, revised the 2016 acute exacerbation (AE) definition—previously limited to idiopathic pulmonary fibrosis (IPF)—into an AE-fILD definition applicable across all fibrotic interstitial lung diseases (anchored in diffuse alveolar damage with or without organizing pneumonia), proposed the broader concept of acute respiratory worsening (ARW) to capture acute deteriorations not attributable to DAD, and summarized evidence on epidemiology, risk factors, prognosis, and management while discussing AE as a clinical trial endpoint.
An international multidisciplinary working group of 41 experts systematically reviewed 922 citations up to March 17, 2025, revised the 2016 acute exacerbation (AE) definition—previously limited to idiopathic pulmonary fibrosis (IPF)—into an AE-fILD definition applicable across all fibrotic interstitial lung diseases (anchored in diffuse alveolar damage with or without organizing pneumonia), proposed the broader concept of acute respiratory worsening (ARW) to capture acute deteriorations not attributable to DAD, and summarized evidence on epidemiology, risk factors, prognosis, and management while discussing AE as a clinical trial endpoint.
Investigative Radiology In a two-center study of 378 patients with focal hepatic lesions (190 benign, 227 lesions; 188 malignant, 2681 lesions), radiomic features were extracted from nine PCD-CT spectral datasets (40, 50, 70, 90, 110, 140, 180 keV, virtual non-contrast [VNC], and iodine density maps [IDM]) after nnU-Net segmentation confirmed by an abdominal radiologist, multiple machine-learning models were trained with lesion-level predictions aggregated per patient, and the Random Forest model trained on VNC achieved the highest performance (AUC 0.899; 95% CI 0.840-0.951; accuracy 83.5%), while cross-domain analysis showed similar mean AUCs across training reconstructions (0.75 to 0.83) and test reconstruction choice mattered: 110, 140, 180 keV and VNC were most stable (median AUC >= 0.
In a two-center study of 378 patients with focal hepatic lesions (190 benign, 227 lesions; 188 malignant, 2681 lesions), radiomic features were extracted from nine PCD-CT spectral datasets (40, 50, 70, 90, 110, 140, 180 keV, virtual non-contrast [VNC], and iodine density maps [IDM]) after nnU-Net segmentation confirmed by an abdominal radiologist, multiple machine-learning models were trained with lesion-level predictions aggregated per patient, and the Random Forest model trained on VNC achieved the highest performance (AUC 0.899; 95% CI 0.840-0.951; accuracy 83.5%), while cross-domain analysis showed similar mean AUCs across training reconstructions (0.75 to 0.83) and test reconstruction choice mattered: 110, 140, 180 keV and VNC were most stable (median AUC >= 0.
In a two-center study of 378 patients with focal hepatic lesions (190 benign, 227 lesions; 188 malignant, 2681 lesions), radiomic features were extracted from nine PCD-CT spectral datasets (40, 50, 70, 90, 110, 140, 180 keV, virtual non-contrast [VNC], and iodine density maps [IDM]) after nnU-Net segmentation confirmed by an abdominal radiologist, multiple machine-learning models were trained with lesion-level predictions aggregated per patient, and the Random Forest model trained on VNC achieved the highest performance (AUC 0.899; 95% CI 0.840-0.951; accuracy 83.5%), while cross-domain analysis showed similar mean AUCs across training reconstructions (0.75 to 0.83) and test reconstruction choice mattered: 110, 140, 180 keV and VNC were most stable (median AUC >= 0.
In a two-center study of 378 patients with focal hepatic lesions (190 benign, 227 lesions; 188 malignant, 2681 lesions), radiomic features were extracted from nine PCD-CT spectral datasets (40, 50, 70, 90, 110, 140, 180 keV, virtual non-contrast [VNC], and iodine density maps [IDM]) after nnU-Net segmentation confirmed by an abdominal radiologist, multiple machine-learning models were trained with lesion-level predictions aggregated per patient, and the Random Forest model trained on VNC achieved the highest performance (AUC 0.899; 95% CI 0.840-0.951; accuracy 83.5%), while cross-domain analysis showed similar mean AUCs across training reconstructions (0.75 to 0.83) and test reconstruction choice mattered: 110, 140, 180 keV and VNC were most stable (median AUC >= 0.
European Journal Pharmaceutical and Medical Research This review discusses the fundamental concepts, workflow, statistical tools, applications, regulatory significance, advantages, challenges, and future perspectives of Analytical Quality by Design (AQbD), noting that AQbD generally begins with defining an Analytical Target Profile (ATP) and proceeds through identification of critical analytical attributes and performance characteristics, risk assessment, identification of critical method parameters, application of Design of Experiments (DoE), establishment of a Method Operable Design Region (MODR), and development of an analytical control strategy, and suggesting that integration of AQbD with multivariate analysis, chemometrics, automation, artificial intelligence, machine learning, green analytical chemistry, and real-time analytical techn
This review discusses the fundamental concepts, workflow, statistical tools, applications, regulatory significance, advantages, challenges, and future perspectives of Analytical Quality by Design (AQbD), noting that AQbD generally begins with defining an Analytical Target Profile (ATP) and proceeds through identification of critical analytical attributes and performance characteristics, risk assessment, identification of critical method parameters, application of Design of Experiments (DoE), establishment of a Method Operable Design Region (MODR), and development of an analytical control strategy, and suggesting that integration of AQbD with multivariate analysis, chemometrics, automation, artificial intelligence, machine learning, green analytical chemistry, and real-time analytical techn
This review discusses the fundamental concepts, workflow, statistical tools, applications, regulatory significance, advantages, challenges, and future perspectives of Analytical Quality by Design (AQbD), noting that AQbD generally begins with defining an Analytical Target Profile (ATP) and proceeds through identification of critical analytical attributes and performance characteristics, risk assessment, identification of critical method parameters, application of Design of Experiments (DoE), establishment of a Method Operable Design Region (MODR), and development of an analytical control strategy, and suggesting that integration of AQbD with multivariate analysis, chemometrics, automation, artificial intelligence, machine learning, green analytical chemistry, and real-time analytical techn
This review discusses the fundamental concepts, workflow, statistical tools, applications, regulatory significance, advantages, challenges, and future perspectives of Analytical Quality by Design (AQbD), noting that AQbD generally begins with defining an Analytical Target Profile (ATP) and proceeds through identification of critical analytical attributes and performance characteristics, risk assessment, identification of critical method parameters, application of Design of Experiments (DoE), establishment of a Method Operable Design Region (MODR), and development of an analytical control strategy, and suggesting that integration of AQbD with multivariate analysis, chemometrics, automation, artificial intelligence, machine learning, green analytical chemistry, and real-time analytical techn
American Journal of Respiratory and Critical Care Medicine Using an unbiased druggable-genome siRNA screen, this study identified ADAMTS14 as a regulator of YAP nuclear translocation; single-cell and spatial transcriptomics of IPF patient lungs localized ADAMTS14 to a CTHRC1-high myofibroblast population enriched in fibroblastic foci, and knockdown or knockout of ADAMTS14 in IPF patient-derived lung fibroblasts reduced pro-fibrotic, matrisome, and TGFβ-response gene expression; mechanistically, collagen V was identified as an ADAMTS14 substrate whose impaired processing shifted the COL1:COL5 ratio from about 50:1 to about 20:1, producing an unstable matrix with disorganized focal adhesions and reduced FAK-AKT signaling and force transmission.
Using an unbiased druggable-genome siRNA screen, this study identified ADAMTS14 as a regulator of YAP nuclear translocation; single-cell and spatial transcriptomics of IPF patient lungs localized ADAMTS14 to a CTHRC1-high myofibroblast population enriched in fibroblastic foci, and knockdown or knockout of ADAMTS14 in IPF patient-derived lung fibroblasts reduced pro-fibrotic, matrisome, and TGFβ-response gene expression; mechanistically, collagen V was identified as an ADAMTS14 substrate whose impaired processing shifted the COL1:COL5 ratio from about 50:1 to about 20:1, producing an unstable matrix with disorganized focal adhesions and reduced FAK-AKT signaling and force transmission.
Using an unbiased druggable-genome siRNA screen, this study identified ADAMTS14 as a regulator of YAP nuclear translocation; single-cell and spatial transcriptomics of IPF patient lungs localized ADAMTS14 to a CTHRC1-high myofibroblast population enriched in fibroblastic foci, and knockdown or knockout of ADAMTS14 in IPF patient-derived lung fibroblasts reduced pro-fibrotic, matrisome, and TGFβ-response gene expression; mechanistically, collagen V was identified as an ADAMTS14 substrate whose impaired processing shifted the COL1:COL5 ratio from about 50:1 to about 20:1, producing an unstable matrix with disorganized focal adhesions and reduced FAK-AKT signaling and force transmission.
Using an unbiased druggable-genome siRNA screen, this study identified ADAMTS14 as a regulator of YAP nuclear translocation; single-cell and spatial transcriptomics of IPF patient lungs localized ADAMTS14 to a CTHRC1-high myofibroblast population enriched in fibroblastic foci, and knockdown or knockout of ADAMTS14 in IPF patient-derived lung fibroblasts reduced pro-fibrotic, matrisome, and TGFβ-response gene expression; mechanistically, collagen V was identified as an ADAMTS14 substrate whose impaired processing shifted the COL1:COL5 ratio from about 50:1 to about 20:1, producing an unstable matrix with disorganized focal adhesions and reduced FAK-AKT signaling and force transmission.
European Journal Pharmaceutical and Medical Research This review examines artificial intelligence in personalized medicine across biomarker discovery, disease subtyping, risk prediction, early diagnosis, treatment-response modelling, pharmacogenomics, digital pathology, longitudinal monitoring, and clinical decision support, and discusses the data types enabling personalization, the conceptual foundations, unresolved ethical and legal issues, and the obstacles between research potential and clinical practice, while emphasizing that AI does not take over the doctor's decision-making but helps doctors access more information than they could retain within their minds all at once.
This review examines artificial intelligence in personalized medicine across biomarker discovery, disease subtyping, risk prediction, early diagnosis, treatment-response modelling, pharmacogenomics, digital pathology, longitudinal monitoring, and clinical decision support, and discusses the data types enabling personalization, the conceptual foundations, unresolved ethical and legal issues, and the obstacles between research potential and clinical practice, while emphasizing that AI does not take over the doctor's decision-making but helps doctors access more information than they could retain within their minds all at once.
This review examines artificial intelligence in personalized medicine across biomarker discovery, disease subtyping, risk prediction, early diagnosis, treatment-response modelling, pharmacogenomics, digital pathology, longitudinal monitoring, and clinical decision support, and discusses the data types enabling personalization, the conceptual foundations, unresolved ethical and legal issues, and the obstacles between research potential and clinical practice, while emphasizing that AI does not take over the doctor's decision-making but helps doctors access more information than they could retain within their minds all at once.
This review examines artificial intelligence in personalized medicine across biomarker discovery, disease subtyping, risk prediction, early diagnosis, treatment-response modelling, pharmacogenomics, digital pathology, longitudinal monitoring, and clinical decision support, and discusses the data types enabling personalization, the conceptual foundations, unresolved ethical and legal issues, and the obstacles between research potential and clinical practice, while emphasizing that AI does not take over the doctor's decision-making but helps doctors access more information than they could retain within their minds all at once.
DOAJ (DOAJ: Directory of Open Access Journals) The work is titled 'Mapping and Analysis of Global Research Trends on Strategizing: A Scientometric Approach' and sets out to map and analyze global research trends on strategizing using scientometric methods; however, the loaded text is only a reference list containing strategy-as-practice scholarship by Whittington, Jarzabkowski, Vaara, and Seidl alongside methodological sources such as Aria & Cuccurullo's Bibliometrix and Zupic & Čater's bibliometric methods review, with no abstract, data source, search strategy, sample size, results, or conclusions, so what the study actually did and found cannot be extracted from this text.
The work is titled 'Mapping and Analysis of Global Research Trends on Strategizing: A Scientometric Approach' and sets out to map and analyze global research trends on strategizing using scientometric methods; however, the loaded text is only a reference list containing strategy-as-practice scholarship by Whittington, Jarzabkowski, Vaara, and Seidl alongside methodological sources such as Aria & Cuccurullo's Bibliometrix and Zupic & Čater's bibliometric methods review, with no abstract, data source, search strategy, sample size, results, or conclusions, so what the study actually did and found cannot be extracted from this text.
The work is titled 'Mapping and Analysis of Global Research Trends on Strategizing: A Scientometric Approach' and sets out to map and analyze global research trends on strategizing using scientometric methods; however, the loaded text is only a reference list containing strategy-as-practice scholarship by Whittington, Jarzabkowski, Vaara, and Seidl alongside methodological sources such as Aria & Cuccurullo's Bibliometrix and Zupic & Čater's bibliometric methods review, with no abstract, data source, search strategy, sample size, results, or conclusions, so what the study actually did and found cannot be extracted from this text.
The work is titled 'Mapping and Analysis of Global Research Trends on Strategizing: A Scientometric Approach' and sets out to map and analyze global research trends on strategizing using scientometric methods; however, the loaded text is only a reference list containing strategy-as-practice scholarship by Whittington, Jarzabkowski, Vaara, and Seidl alongside methodological sources such as Aria & Cuccurullo's Bibliometrix and Zupic & Čater's bibliometric methods review, with no abstract, data source, search strategy, sample size, results, or conclusions, so what the study actually did and found cannot be extracted from this text.
American Journal of Respiratory Cell and Molecular Biology Combining human cord blood monocytes with a neonatal mouse influenza model, this study found that neonatal monocytes sustain higher TLR2 expression after LTA or IAV stimulation, while TLR2 gene deletion, anti-TLR2 antibody blockade, or myeloid-specific TLR2 deletion improved survival of IAV-infected neonatal mice (for example, 61% versus 25% survival for TLR2−/− versus wild-type neonates, and 46% versus 7% with anti-TLR2 antibody), accompanied by reduced neutrophils at 6 days post-infection, lower histopathology scores in myeloid conditional knockouts, and no further rise in IL-6, TNF-α, MCP-1, CXCL1, and CXCL2 from 3 to 6 days post-infection, suggesting that myeloid TLR2 signaling exacerbates neonatal susceptibility to respiratory viral infection by amplifying pulmonary inflammation.
Combining human cord blood monocytes with a neonatal mouse influenza model, this study found that neonatal monocytes sustain higher TLR2 expression after LTA or IAV stimulation, while TLR2 gene deletion, anti-TLR2 antibody blockade, or myeloid-specific TLR2 deletion improved survival of IAV-infected neonatal mice (for example, 61% versus 25% survival for TLR2−/− versus wild-type neonates, and 46% versus 7% with anti-TLR2 antibody), accompanied by reduced neutrophils at 6 days post-infection, lower histopathology scores in myeloid conditional knockouts, and no further rise in IL-6, TNF-α, MCP-1, CXCL1, and CXCL2 from 3 to 6 days post-infection, suggesting that myeloid TLR2 signaling exacerbates neonatal susceptibility to respiratory viral infection by amplifying pulmonary inflammation.
Combining human cord blood monocytes with a neonatal mouse influenza model, this study found that neonatal monocytes sustain higher TLR2 expression after LTA or IAV stimulation, while TLR2 gene deletion, anti-TLR2 antibody blockade, or myeloid-specific TLR2 deletion improved survival of IAV-infected neonatal mice (for example, 61% versus 25% survival for TLR2−/− versus wild-type neonates, and 46% versus 7% with anti-TLR2 antibody), accompanied by reduced neutrophils at 6 days post-infection, lower histopathology scores in myeloid conditional knockouts, and no further rise in IL-6, TNF-α, MCP-1, CXCL1, and CXCL2 from 3 to 6 days post-infection, suggesting that myeloid TLR2 signaling exacerbates neonatal susceptibility to respiratory viral infection by amplifying pulmonary inflammation.
Combining human cord blood monocytes with a neonatal mouse influenza model, this study found that neonatal monocytes sustain higher TLR2 expression after LTA or IAV stimulation, while TLR2 gene deletion, anti-TLR2 antibody blockade, or myeloid-specific TLR2 deletion improved survival of IAV-infected neonatal mice (for example, 61% versus 25% survival for TLR2−/− versus wild-type neonates, and 46% versus 7% with anti-TLR2 antibody), accompanied by reduced neutrophils at 6 days post-infection, lower histopathology scores in myeloid conditional knockouts, and no further rise in IL-6, TNF-α, MCP-1, CXCL1, and CXCL2 from 3 to 6 days post-infection, suggesting that myeloid TLR2 signaling exacerbates neonatal susceptibility to respiratory viral infection by amplifying pulmonary inflammation.