Body movements and posture provide valuable insights into stress responses, yet their relationship with endocrine biomarkers of the stress response remains underexplored. This study investigates whether movement patterns during the Trier Social Stres...
OBJECTIVE: To develop and validate a computerized tomography (CT)‑based deep transfer learning radiomics model combined with explainable machine learning for preoperative risk prediction of thymoma.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jun 26, 2025
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...
Journal of chemical information and modeling
Jun 26, 2025
Scaffold hopping-the design of novel scaffolds for existing lead candidates-is a multifaceted and nontrivial task, for medicinal chemists and computational approaches alike. Generative reinforcement learning can iteratively optimize desirable propert...
Journal of chemical information and modeling
Jun 26, 2025
RNA molecules exhibit diverse structures and functions, making them promising drug targets. However, predicting RNA-small molecule binding affinity remains challenging due to limited experimental data and the structural variability introduced by mult...
OBJECTIVE: Machine learning (ML) models have emerged as tools to predict length of stay (LOS) and disposition decision (DD) in emergency departments (EDs) to combat overcrowding. However, site-specific ML models are not transferable to different site...
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...
BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practi...
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...
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