Medicine & Health

This work prospectively collected 8,181 frames from 455 patients during routine colonoscopy at Farhikhtegan Hospital, Tehran, Iran, between February and December 2025 (432 polyp-positive frames with expert pixel-level segmentation masks and 7,749 normal-mucosa frames), linked patient-level metadata (age, sex, colonoscopy indication, BBPS score, and procedure duration) to every case, and trained and evaluated six segmentation architectures under one standardized protocol with patient-grouped five-fold cross-validation, finding that PraNet reached the highest internal Dice (0.755) and nnU-Net the highest internal IoU (0.665) and pixel accuracy, yet gated false-positive rates on normal mucosa ranged from 24.9% (YOLOv11m-seg) to 59.

Using cerastecin Cpd 4 as a template, this study applied two AI tools, Link-INVENT and AutoMolDesigner, for molecular design and chemical derivatization, leading to the discovery of the MsbA-targeted small molecule Y-11 with an MIC of 0.5 g/mL against A. baumannii, equivalent potency to Cpd4 against carbapenem-resistant A. baumannii, lower cytotoxicity, hemolysis, and spontaneous resistance frequency, effective reduction of bacterial loads in infected mice, and a proposed mechanism in which Y-11 inhibits lipooligosaccharide transport and impairs outer membrane formation, probably by competitively binding the substrate binding site of MsbA and modulating ATPase activity.

In this prospective cohort study, 96 patients with spinal pain completed an extensive questionnaire covering pain, mood, sleep, lifestyle, and treatment expectations at baseline and at 1 and 3 months, with binary recovery outcomes defined at 3 months for pain intensity, disability, quality of life, and Patient Global Impression of Change; a three-step machine learning framework combining SHAP-based candidate feature selection, Leave-One-Out Cross-Validation with permutation testing, and generalization testing yielded AUC values of 0.93-0.99 in LOOCV and 0.62-0.

Using the Japanese JAMDAS electronic medical records database, this retrospective observational study analyzed 32,258 patients with asthma who initiated fluticasone furoate/umeclidinium/vilanterol single-inhaler triple therapy between August 18, 2020 and December 31, 2024, extracting Asthma Control Test scores via structured query language and hospitalization and emergency transport data via a large language model, and assessed the proportion meeting the Japanese Practical Guidelines for Asthma Management 2024 clinical remission definition (oral corticosteroid-free, no exacerbations, ACT >= 23), treatment patterns, adherence and persistence at 3-month intervals up to 18 months; only 1.8-3.0%, 0.5-1.5% and 4.5-10.

This retrospective study analyzed 4027 consecutive non-contrast head CT examinations from a large emergency hospital in southwest Sweden to compare three commercial AI algorithms for ICH detection, finding substantial variation with only Aidoc demonstrating clinically relevant accuracy (90.3% sensitivity, 99.0% specificity), while a simulated mathematical combination of Aidoc with a human reader increased sensitivity to 96.0% while maintaining 99.4% specificity (P < 0.001), comparable to two radiologists.

In this retrospective multicenter study, an in-house deep learning segmentation model delineated the zona pellucida, inner cell mass, and trophectoderm and extracted 17 quantitative morphological indicators from 14,072 blastocyst images across seven Korean centers (after exclusions, 10,718 embryos for consensus grade prediction and 1,387 for fetal heart tone prediction), finding that morphology-based predicted grades agreed with consensus grades more closely than individual embryologists for developmental stage and inner cell mass, and that a quantitative morphology-based Random Forest model outperformed a manual consensus grade-based model for fetal heart tone prediction (AUROC 0.648 versus 0.610; DeLong's test p = 0.

This study developed and dual-center validated an interpretable U-Net-based AI framework for automated quality control (QC) of knee anteroposterior (AP) and lateral (LAT) radiographs, generating QC indices through anatomical segmentation and landmark localization, with mean Dice similarity coefficients of 0.964 and 0.936 in internal and external validation, most intraclass correlation coefficients exceeding 0.90, QC sensitivity of 91.67% to 98.36% and specificity of 89.13% to 99.10%; separately, six radiographers who received 4 weeks of AI-based feedback on 948 radiographs from 474 patients showed exploratory numerical gains in sensitivity, with effect sizes of 0.30 to 0.73.

This American Heart Association scientific statement summarizes the current epidemiology of cardiovascular disease and stroke among Hispanic/Latino adults in the United States, noting that cardiovascular disease became the leading cause of death in this population in 2022, that Hispanic adults carry a disproportionate burden of cardiometabolic risk factors including obesity, diabetes, and dyslipidemia, and that substantial differences exist across Hispanic heritage groups, sexes, and disease types, such that the "Hispanic paradox" is increasingly seen as an oversimplification; it further sets priorities including expanding disaggregated data collection, increasing research representation, and ensuring equitable implementation of precision medicine approaches including genomics, multi-omics