Medicine & Health

455 items

Frontiers in Endocrinology Sep 28, 2026
Using retrospective single-center data from 1,319 patients undergoing their first frozen embryo transfer at Guangdong Provincial Hospital of Chinese Medicine, split by transfer date into a training cohort (n=1,013) and a temporal validation cohort (n=306), the authors used LASSO to select age, induced abortions, cycle type, good-quality embryos, transferred embryos, endometrial change, BMI, antral follicle count, embryo transfer-day endometrial thickness, and retrieval-transfer interval, then developed an XGBoost model and compared it with logistic regression; XGBoost achieved an AUC of 0.854 (95% CI 0.832-0.877) in training and 0.722 (95% CI 0.666-0.779) in temporal validation, with AUPRC values of 0.840 and 0.707, acceptable calibration in validation (Brier score 0.212, intercept 0.
Using retrospective single-center data from 1,319 patients undergoing their first frozen embryo transfer at Guangdong Provincial Hospital of Chinese Medicine, split by transfer date into a training cohort (n=1,013) and a temporal validation cohort (n=306), the authors used LASSO to select age, induced abortions, cycle type, good-quality embryos, transferred embryos, endometrial change, BMI, antral follicle count, embryo transfer-day endometrial thickness, and retrieval-transfer interval, then developed an XGBoost model and compared it with logistic regression; XGBoost achieved an AUC of 0.854 (95% CI 0.832-0.877) in training and 0.722 (95% CI 0.666-0.779) in temporal validation, with AUPRC values of 0.840 and 0.707, acceptable calibration in validation (Brier score 0.212, intercept 0.
Explainable XGBoost model predicts clinical pregnancy after frozen embryo transfer in 1,319 single-center cases, with AUC falling from 0.854 to 0.722 in temporal validation
Using retrospective single-center data from 1,319 patients undergoing their first frozen embryo transfer at Guangdong Provincial Hospital of Chinese Medicine, split by transfer date into a training cohort (n=1,013) and a temporal validation cohort (n=306), the authors used LASSO to select age, induced abortions, cycle type, good-quality embryos, transferred embryos, endometrial change, BMI, antral follicle count, embryo transfer-day endometrial thickness, and retrieval-transfer interval, then developed an XGBoost model and compared it with logistic regression; XGBoost achieved an AUC of 0.854 (95% CI 0.832-0.877) in training and 0.722 (95% CI 0.666-0.779) in temporal validation, with AUPRC values of 0.840 and 0.707, acceptable calibration in validation (Brier score 0.212, intercept 0.
Using retrospective single-center data from 1,319 patients undergoing their first frozen embryo transfer at Guangdong Provincial Hospital of Chinese Medicine, split by transfer date into a training cohort (n=1,013) and a temporal validation cohort (n=306), the authors used LASSO to select age, induced abortions, cycle type, good-quality embryos, transferred embryos, endometrial change, BMI, antral follicle count, embryo transfer-day endometrial thickness, and retrieval-transfer interval, then developed an XGBoost model and compared it with logistic regression; XGBoost achieved an AUC of 0.854 (95% CI 0.832-0.877) in training and 0.722 (95% CI 0.666-0.779) in temporal validation, with AUPRC values of 0.840 and 0.707, acceptable calibration in validation (Brier score 0.212, intercept 0.
BJPsych open Sep 28, 2026
The protocol describes the design of the 5W-PL study: using the Centre for Victorian Data Linkage's Victorian Linkage Map to link 14 datasets covering mortality, mental health, hospital, emergency, ambulance and human services (child protection, disability, sexual assault, homelessness, alcohol and drug) through deterministic and probabilistic methods, building a cross-sector longitudinal cohort of people born between 1970 and 2010 with service-use records from 2015 to 2025, in order to identify subgroups by care pathway, map geographical patterns of service need, and develop predictive models of service type and intensity for young people aged 12–25.
The protocol describes the design of the 5W-PL study: using the Centre for Victorian Data Linkage's Victorian Linkage Map to link 14 datasets covering mortality, mental health, hospital, emergency, ambulance and human services (child protection, disability, sexual assault, homelessness, alcohol and drug) through deterministic and probabilistic methods, building a cross-sector longitudinal cohort of people born between 1970 and 2010 with service-use records from 2015 to 2025, in order to identify subgroups by care pathway, map geographical patterns of service need, and develop predictive models of service type and intensity for young people aged 12–25.
Australian team publishes the 5W-PL protocol: linking 14 Victorian health and human services datasets to trace mental health service pathways for young people aged 12–25
The protocol describes the design of the 5W-PL study: using the Centre for Victorian Data Linkage's Victorian Linkage Map to link 14 datasets covering mortality, mental health, hospital, emergency, ambulance and human services (child protection, disability, sexual assault, homelessness, alcohol and drug) through deterministic and probabilistic methods, building a cross-sector longitudinal cohort of people born between 1970 and 2010 with service-use records from 2015 to 2025, in order to identify subgroups by care pathway, map geographical patterns of service need, and develop predictive models of service type and intensity for young people aged 12–25.
The protocol describes the design of the 5W-PL study: using the Centre for Victorian Data Linkage's Victorian Linkage Map to link 14 datasets covering mortality, mental health, hospital, emergency, ambulance and human services (child protection, disability, sexual assault, homelessness, alcohol and drug) through deterministic and probabilistic methods, building a cross-sector longitudinal cohort of people born between 1970 and 2010 with service-use records from 2015 to 2025, in order to identify subgroups by care pathway, map geographical patterns of service need, and develop predictive models of service type and intensity for young people aged 12–25.
Research Square Sep 28, 2026
Using retrospective data from 100 patients who underwent transsphenoidal endoscopic pituitary tumor resection between 2016 and 2025, the study extracted 22 preoperative variables and developed and evaluated an artificial neural network and a random forest model against R², MAE, RMSE, and clinical accuracy thresholds of ±30 and ±45 minutes; the ANN outperformed random forest with a test-set MAE of 0.636 hours (about 38 minutes), 63.3% of predictions fell within ±30 minutes and 76.7% within ±45 minutes, and key predictors included tumor recurrence, distance from the third ventricle floor, and the cinch sign, which the authors present as objective evidence for nursing scheduling and operating room planning.
Using retrospective data from 100 patients who underwent transsphenoidal endoscopic pituitary tumor resection between 2016 and 2025, the study extracted 22 preoperative variables and developed and evaluated an artificial neural network and a random forest model against R², MAE, RMSE, and clinical accuracy thresholds of ±30 and ±45 minutes; the ANN outperformed random forest with a test-set MAE of 0.636 hours (about 38 minutes), 63.3% of predictions fell within ±30 minutes and 76.7% within ±45 minutes, and key predictors included tumor recurrence, distance from the third ventricle floor, and the cinch sign, which the authors present as objective evidence for nursing scheduling and operating room planning.
An artificial neural network predicted transsphenoidal endoscopic pituitary adenomectomy duration with a test-set mean absolute error of about 38 minutes
Using retrospective data from 100 patients who underwent transsphenoidal endoscopic pituitary tumor resection between 2016 and 2025, the study extracted 22 preoperative variables and developed and evaluated an artificial neural network and a random forest model against R², MAE, RMSE, and clinical accuracy thresholds of ±30 and ±45 minutes; the ANN outperformed random forest with a test-set MAE of 0.636 hours (about 38 minutes), 63.3% of predictions fell within ±30 minutes and 76.7% within ±45 minutes, and key predictors included tumor recurrence, distance from the third ventricle floor, and the cinch sign, which the authors present as objective evidence for nursing scheduling and operating room planning.
Using retrospective data from 100 patients who underwent transsphenoidal endoscopic pituitary tumor resection between 2016 and 2025, the study extracted 22 preoperative variables and developed and evaluated an artificial neural network and a random forest model against R², MAE, RMSE, and clinical accuracy thresholds of ±30 and ±45 minutes; the ANN outperformed random forest with a test-set MAE of 0.636 hours (about 38 minutes), 63.3% of predictions fell within ±30 minutes and 76.7% within ±45 minutes, and key predictors included tumor recurrence, distance from the third ventricle floor, and the cinch sign, which the authors present as objective evidence for nursing scheduling and operating room planning.
Frontiers in Pharmacology Sep 28, 2026
This narrative review traces TDDS evaluation from pre-1975 methodological fragmentation through Franz diffusion cell and IVPT standardization to RHE, full-thickness skin models, ex vivo human skin and iPSC-derived skin organoids (SkOs), reporting that SkOs self-organize stratified epidermis, dermal-like structures, hair follicles and sebaceous glands and that after roughly 4-5 months in culture their transcriptome resembles second-trimester human fetal skin, but that the authors' search identified no clear study using Lee-type hiPSC-derived SkOs as standardized barrier models in Franz diffusion cells or conventional IVPT with systematic measurement of cumulative permeation, steady-state flux, permeability coefficient or skin retention, concluding that SkOs are a frontier candidate rather t
This narrative review traces TDDS evaluation from pre-1975 methodological fragmentation through Franz diffusion cell and IVPT standardization to RHE, full-thickness skin models, ex vivo human skin and iPSC-derived skin organoids (SkOs), reporting that SkOs self-organize stratified epidermis, dermal-like structures, hair follicles and sebaceous glands and that after roughly 4-5 months in culture their transcriptome resembles second-trimester human fetal skin, but that the authors' search identified no clear study using Lee-type hiPSC-derived SkOs as standardized barrier models in Franz diffusion cells or conventional IVPT with systematic measurement of cumulative permeation, steady-state flux, permeability coefficient or skin retention, concluding that SkOs are a frontier candidate rather t
Review reports that iPSC-derived skin organoids self-assemble hair follicles and sebaceous glands, yet no study has used them for standardized Franz diffusion cell or IVPT permeation parameters
This narrative review traces TDDS evaluation from pre-1975 methodological fragmentation through Franz diffusion cell and IVPT standardization to RHE, full-thickness skin models, ex vivo human skin and iPSC-derived skin organoids (SkOs), reporting that SkOs self-organize stratified epidermis, dermal-like structures, hair follicles and sebaceous glands and that after roughly 4-5 months in culture their transcriptome resembles second-trimester human fetal skin, but that the authors' search identified no clear study using Lee-type hiPSC-derived SkOs as standardized barrier models in Franz diffusion cells or conventional IVPT with systematic measurement of cumulative permeation, steady-state flux, permeability coefficient or skin retention, concluding that SkOs are a frontier candidate rather t
This narrative review traces TDDS evaluation from pre-1975 methodological fragmentation through Franz diffusion cell and IVPT standardization to RHE, full-thickness skin models, ex vivo human skin and iPSC-derived skin organoids (SkOs), reporting that SkOs self-organize stratified epidermis, dermal-like structures, hair follicles and sebaceous glands and that after roughly 4-5 months in culture their transcriptome resembles second-trimester human fetal skin, but that the authors' search identified no clear study using Lee-type hiPSC-derived SkOs as standardized barrier models in Franz diffusion cells or conventional IVPT with systematic measurement of cumulative permeation, steady-state flux, permeability coefficient or skin retention, concluding that SkOs are a frontier candidate rather t
Frontiers in Oncology Sep 28, 2026
Using Scopus and Web of Science and a PRISMA workflow that narrowed 4,831 records to 608 peer-reviewed journal articles and reviews from 2020 to 2026, this study applied Bibliometrix and VOSviewer for a task-aware, methodology-centric bibliometric and thematic analysis, finding that diagnosis accounts for 71.22% of studies, mammography for 42.11%, explainable AI shows the strongest burst ratio at 1.00, while treatment-response prediction covers only 2.30% and only about 15-25% of studies explicitly report hyperparameter tuning strategies.
Using Scopus and Web of Science and a PRISMA workflow that narrowed 4,831 records to 608 peer-reviewed journal articles and reviews from 2020 to 2026, this study applied Bibliometrix and VOSviewer for a task-aware, methodology-centric bibliometric and thematic analysis, finding that diagnosis accounts for 71.22% of studies, mammography for 42.11%, explainable AI shows the strongest burst ratio at 1.00, while treatment-response prediction covers only 2.30% and only about 15-25% of studies explicitly report hyperparameter tuning strategies.
Bibliometric analysis of 608 AI breast cancer imaging studies finds diagnosis at 71.22% and explainable AI with a 1.00 burst ratio as the hottest frontier
Using Scopus and Web of Science and a PRISMA workflow that narrowed 4,831 records to 608 peer-reviewed journal articles and reviews from 2020 to 2026, this study applied Bibliometrix and VOSviewer for a task-aware, methodology-centric bibliometric and thematic analysis, finding that diagnosis accounts for 71.22% of studies, mammography for 42.11%, explainable AI shows the strongest burst ratio at 1.00, while treatment-response prediction covers only 2.30% and only about 15-25% of studies explicitly report hyperparameter tuning strategies.
Using Scopus and Web of Science and a PRISMA workflow that narrowed 4,831 records to 608 peer-reviewed journal articles and reviews from 2020 to 2026, this study applied Bibliometrix and VOSviewer for a task-aware, methodology-centric bibliometric and thematic analysis, finding that diagnosis accounts for 71.22% of studies, mammography for 42.11%, explainable AI shows the strongest burst ratio at 1.00, while treatment-response prediction covers only 2.30% and only about 15-25% of studies explicitly report hyperparameter tuning strategies.
Frontiers in Medicine Sep 28, 2026
Using data reconstructed from Wang et al.'s supplementary tables, this study built 161 loading-capacity observations with 110 descriptors and 444 cell-viability observations with 25 descriptors, optimized histogram-based gradient boosting regression (HGBR) and partial least squares regression (PLSR) with differential evolution under five-fold grouped cross-validation, and constrained exact duplicate records to the same partition to prevent information leakage; on the duplicate-safe 20% holdout HGBR was strongest for cell viability (R² = 0.774, RMSE = 11.655 percentage points, MAE = 8.153, AARD = 16.69%) while PLSR was best for loading capacity (R² = 0.557, RMSE = 0.345 g/g, MAE = 0.210 g/g), yet holding out entire source publications drove all R² values negative (viability −0.391 and −0.
Using data reconstructed from Wang et al.'s supplementary tables, this study built 161 loading-capacity observations with 110 descriptors and 444 cell-viability observations with 25 descriptors, optimized histogram-based gradient boosting regression (HGBR) and partial least squares regression (PLSR) with differential evolution under five-fold grouped cross-validation, and constrained exact duplicate records to the same partition to prevent information leakage; on the duplicate-safe 20% holdout HGBR was strongest for cell viability (R² = 0.774, RMSE = 11.655 percentage points, MAE = 8.153, AARD = 16.69%) while PLSR was best for loading capacity (R² = 0.557, RMSE = 0.345 g/g, MAE = 0.210 g/g), yet holding out entire source publications drove all R² values negative (viability −0.391 and −0.
Leakage-aware ML predicts MOF drug loading and cell viability at in-domain R² of 0.557 and 0.774, but R² turns negative when whole publications are held out
Using data reconstructed from Wang et al.'s supplementary tables, this study built 161 loading-capacity observations with 110 descriptors and 444 cell-viability observations with 25 descriptors, optimized histogram-based gradient boosting regression (HGBR) and partial least squares regression (PLSR) with differential evolution under five-fold grouped cross-validation, and constrained exact duplicate records to the same partition to prevent information leakage; on the duplicate-safe 20% holdout HGBR was strongest for cell viability (R² = 0.774, RMSE = 11.655 percentage points, MAE = 8.153, AARD = 16.69%) while PLSR was best for loading capacity (R² = 0.557, RMSE = 0.345 g/g, MAE = 0.210 g/g), yet holding out entire source publications drove all R² values negative (viability −0.391 and −0.
Using data reconstructed from Wang et al.'s supplementary tables, this study built 161 loading-capacity observations with 110 descriptors and 444 cell-viability observations with 25 descriptors, optimized histogram-based gradient boosting regression (HGBR) and partial least squares regression (PLSR) with differential evolution under five-fold grouped cross-validation, and constrained exact duplicate records to the same partition to prevent information leakage; on the duplicate-safe 20% holdout HGBR was strongest for cell viability (R² = 0.774, RMSE = 11.655 percentage points, MAE = 8.153, AARD = 16.69%) while PLSR was best for loading capacity (R² = 0.557, RMSE = 0.345 g/g, MAE = 0.210 g/g), yet holding out entire source publications drove all R² values negative (viability −0.391 and −0.
Neuroscience Research Notes Sep 28, 2026
Addressing the gap in Speech Recognition Threshold (SRT) materials for Greek-speaking school-aged children (6 to 12 years), this study selected words on four criteria—syllabic structure (trisyllabics), age-appropriate vocabulary familiarity, phonemic differentiation, and homogeneity in audibility—recorded and processed them per ISO 8253-3:2022, had 20 children take part in the word homogeneity evaluation, determined for each word the presentation level needed for 50% correct recognition, and measured recognition rates across intensities to locate the steepest rise of the Performance-Intensity (PI) function between 20% and 80% recognition; it found that words homogeneous in recognition rate are not homogeneous in recognition threshold and vice versa, so only words within +1 Standard Deviati
Addressing the gap in Speech Recognition Threshold (SRT) materials for Greek-speaking school-aged children (6 to 12 years), this study selected words on four criteria—syllabic structure (trisyllabics), age-appropriate vocabulary familiarity, phonemic differentiation, and homogeneity in audibility—recorded and processed them per ISO 8253-3:2022, had 20 children take part in the word homogeneity evaluation, determined for each word the presentation level needed for 50% correct recognition, and measured recognition rates across intensities to locate the steepest rise of the Performance-Intensity (PI) function between 20% and 80% recognition; it found that words homogeneous in recognition rate are not homogeneous in recognition threshold and vice versa, so only words within +1 Standard Deviati
Greek trisyllabic word list developed: 40 words retained after testing 20 children aged 6 to 12 for speech recognition threshold
Addressing the gap in Speech Recognition Threshold (SRT) materials for Greek-speaking school-aged children (6 to 12 years), this study selected words on four criteria—syllabic structure (trisyllabics), age-appropriate vocabulary familiarity, phonemic differentiation, and homogeneity in audibility—recorded and processed them per ISO 8253-3:2022, had 20 children take part in the word homogeneity evaluation, determined for each word the presentation level needed for 50% correct recognition, and measured recognition rates across intensities to locate the steepest rise of the Performance-Intensity (PI) function between 20% and 80% recognition; it found that words homogeneous in recognition rate are not homogeneous in recognition threshold and vice versa, so only words within +1 Standard Deviati
Addressing the gap in Speech Recognition Threshold (SRT) materials for Greek-speaking school-aged children (6 to 12 years), this study selected words on four criteria—syllabic structure (trisyllabics), age-appropriate vocabulary familiarity, phonemic differentiation, and homogeneity in audibility—recorded and processed them per ISO 8253-3:2022, had 20 children take part in the word homogeneity evaluation, determined for each word the presentation level needed for 50% correct recognition, and measured recognition rates across intensities to locate the steepest rise of the Performance-Intensity (PI) function between 20% and 80% recognition; it found that words homogeneous in recognition rate are not homogeneous in recognition threshold and vice versa, so only words within +1 Standard Deviati
Research Square Sep 28, 2026
The study proposes TLANet, a three-layer attention-enhanced CNN built from three convolutional feature extraction blocks, channel-spatial attention, global average pooling, and a task-specific classification head, evaluated on two independent ISIC tasks: binary benign/malignant classification on ISIC 2016 (900 train / 379 test images), reporting about 88.3% accuracy, and seven-class diagnosis on ISIC 2018/HAM10000 (10,015 images), reporting a macro F1 of about 0.681, alongside standardized preprocessing, augmentation, baseline comparisons against a no-attention CNN, ResNet, EfficientNet, and MobileNet, ablation, and a full metric suite.
The study proposes TLANet, a three-layer attention-enhanced CNN built from three convolutional feature extraction blocks, channel-spatial attention, global average pooling, and a task-specific classification head, evaluated on two independent ISIC tasks: binary benign/malignant classification on ISIC 2016 (900 train / 379 test images), reporting about 88.3% accuracy, and seven-class diagnosis on ISIC 2018/HAM10000 (10,015 images), reporting a macro F1 of about 0.681, alongside standardized preprocessing, augmentation, baseline comparisons against a no-attention CNN, ResNet, EfficientNet, and MobileNet, ablation, and a full metric suite.
TLANet combines three convolutional blocks with channel-spatial attention, reporting about 88.3% accuracy on ISIC 2016 and a macro F1 of about 0.681 on ISIC 2018
The study proposes TLANet, a three-layer attention-enhanced CNN built from three convolutional feature extraction blocks, channel-spatial attention, global average pooling, and a task-specific classification head, evaluated on two independent ISIC tasks: binary benign/malignant classification on ISIC 2016 (900 train / 379 test images), reporting about 88.3% accuracy, and seven-class diagnosis on ISIC 2018/HAM10000 (10,015 images), reporting a macro F1 of about 0.681, alongside standardized preprocessing, augmentation, baseline comparisons against a no-attention CNN, ResNet, EfficientNet, and MobileNet, ablation, and a full metric suite.
The study proposes TLANet, a three-layer attention-enhanced CNN built from three convolutional feature extraction blocks, channel-spatial attention, global average pooling, and a task-specific classification head, evaluated on two independent ISIC tasks: binary benign/malignant classification on ISIC 2016 (900 train / 379 test images), reporting about 88.3% accuracy, and seven-class diagnosis on ISIC 2018/HAM10000 (10,015 images), reporting a macro F1 of about 0.681, alongside standardized preprocessing, augmentation, baseline comparisons against a no-attention CNN, ResNet, EfficientNet, and MobileNet, ablation, and a full metric suite.
NeuroRegulation Sep 28, 2026
Addressing AI tools entering neuroregulation practice through multiple simultaneous pathways, including automated qEEG analysis, protocol recommendation systems, AI-assisted documentation, and consumer-facing mental health applications that clients bring directly into the therapeutic relationship, and noting that no ethics code specific to neuroregulation has yet addressed these applications directly, Sherlin and Longo present a conceptual and practical ethical framework grounded in the BCIA Code of Ethics, ISNR Code of Ethics, APA Ethical Principles, ACA Code of Ethics, and the APA (2025) Ethical Guidance for Artificial Intelligence, comprising a risk continuum model organizing AI applications along three dimensions of opacity, clinical consequence, and distance from oversight, four ethic
Addressing AI tools entering neuroregulation practice through multiple simultaneous pathways, including automated qEEG analysis, protocol recommendation systems, AI-assisted documentation, and consumer-facing mental health applications that clients bring directly into the therapeutic relationship, and noting that no ethics code specific to neuroregulation has yet addressed these applications directly, Sherlin and Longo present a conceptual and practical ethical framework grounded in the BCIA Code of Ethics, ISNR Code of Ethics, APA Ethical Principles, ACA Code of Ethics, and the APA (2025) Ethical Guidance for Artificial Intelligence, comprising a risk continuum model organizing AI applications along three dimensions of opacity, clinical consequence, and distance from oversight, four ethic
Sherlin and Longo propose an AI ethics framework for neuroregulation practice, pairing a three-dimension risk continuum of opacity, clinical consequence, and distance from oversight with a five-element clinical policy table
Addressing AI tools entering neuroregulation practice through multiple simultaneous pathways, including automated qEEG analysis, protocol recommendation systems, AI-assisted documentation, and consumer-facing mental health applications that clients bring directly into the therapeutic relationship, and noting that no ethics code specific to neuroregulation has yet addressed these applications directly, Sherlin and Longo present a conceptual and practical ethical framework grounded in the BCIA Code of Ethics, ISNR Code of Ethics, APA Ethical Principles, ACA Code of Ethics, and the APA (2025) Ethical Guidance for Artificial Intelligence, comprising a risk continuum model organizing AI applications along three dimensions of opacity, clinical consequence, and distance from oversight, four ethic
Addressing AI tools entering neuroregulation practice through multiple simultaneous pathways, including automated qEEG analysis, protocol recommendation systems, AI-assisted documentation, and consumer-facing mental health applications that clients bring directly into the therapeutic relationship, and noting that no ethics code specific to neuroregulation has yet addressed these applications directly, Sherlin and Longo present a conceptual and practical ethical framework grounded in the BCIA Code of Ethics, ISNR Code of Ethics, APA Ethical Principles, ACA Code of Ethics, and the APA (2025) Ethical Guidance for Artificial Intelligence, comprising a risk continuum model organizing AI applications along three dimensions of opacity, clinical consequence, and distance from oversight, four ethic
医学理论研究 Sep 28, 2026
In a general surgery department of a hospital in Wuchuan, Guangdong, 84 elective surgery patients were allocated by random number table to routine ERAS enhanced recovery nursing or to routine ERAS plus an AI intervention covering preoperative intelligent assessment, postoperative intelligent warning, and continuous intelligent follow-up; the AI group showed higher mean disease knowledge (92.38±3.15 vs 68.12±3.54), lower 24-hour postoperative pain (2.76±1.09 vs 4.81±1.42), shorter time to first ambulation (1.48±0.63 vs 2.88±0.93 days), and higher nursing satisfaction (98.19±1.24 vs 89.17±2.70), all with P<0.05.
In a general surgery department of a hospital in Wuchuan, Guangdong, 84 elective surgery patients were allocated by random number table to routine ERAS enhanced recovery nursing or to routine ERAS plus an AI intervention covering preoperative intelligent assessment, postoperative intelligent warning, and continuous intelligent follow-up; the AI group showed higher mean disease knowledge (92.38±3.15 vs 68.12±3.54), lower 24-hour postoperative pain (2.76±1.09 vs 4.81±1.42), shorter time to first ambulation (1.48±0.63 vs 2.88±0.93 days), and higher nursing satisfaction (98.19±1.24 vs 89.17±2.70), all with P<0.05.
Adding AI intervention to perioperative ERAS nursing in general surgery improved patients' disease knowledge, 24-hour pain, first ambulation time, and satisfaction versus routine care
In a general surgery department of a hospital in Wuchuan, Guangdong, 84 elective surgery patients were allocated by random number table to routine ERAS enhanced recovery nursing or to routine ERAS plus an AI intervention covering preoperative intelligent assessment, postoperative intelligent warning, and continuous intelligent follow-up; the AI group showed higher mean disease knowledge (92.38±3.15 vs 68.12±3.54), lower 24-hour postoperative pain (2.76±1.09 vs 4.81±1.42), shorter time to first ambulation (1.48±0.63 vs 2.88±0.93 days), and higher nursing satisfaction (98.19±1.24 vs 89.17±2.70), all with P<0.05.
In a general surgery department of a hospital in Wuchuan, Guangdong, 84 elective surgery patients were allocated by random number table to routine ERAS enhanced recovery nursing or to routine ERAS plus an AI intervention covering preoperative intelligent assessment, postoperative intelligent warning, and continuous intelligent follow-up; the AI group showed higher mean disease knowledge (92.38±3.15 vs 68.12±3.54), lower 24-hour postoperative pain (2.76±1.09 vs 4.81±1.42), shorter time to first ambulation (1.48±0.63 vs 2.88±0.93 days), and higher nursing satisfaction (98.19±1.24 vs 89.17±2.70), all with P<0.05.

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