AIMC Topic: Machine Learning
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Scaffold Hopping with Generative Reinforcement Learning.
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...
AffiGrapher: Contrastive Heterogeneous Graph Learning with Aromatic Virtual Nodes for RNA-Small Molecule Binding Affinity Prediction.
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...
Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments.
BMJ health & care informatics
Jun 26, 2025
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...
Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.
Pediatric surgery international
Jun 26, 2025
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...
Prognostic predictions in psychosis: exploring the complementary role of machine learning models.
BMJ mental health
Jun 26, 2025
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...
Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.
Biodegradation
Jun 26, 2025
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...
From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.
World journal of urology
Jun 26, 2025
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...
Leveraging transfer learning for efficient bioprinting.
Biofabrication
Jun 26, 2025
Bioprinting is a promising family of processes combining 3D printing with life sciences, offering the potential to significantly advance various applications. Despite numerous research efforts aimed at enhancing process modeling, optimizing capabilit...
A comparative study of fully automatic and semi-automatic methods for oil spill detection using Sentinel-1 data.
Environmental monitoring and assessment
Jun 26, 2025
The oil spill detection and assessment study conducted in the Banten Province of Indonesia involves the application of Sentinel-1 satellite data and machine learning tools in the year 2024. Synthetic Aperture Radar (SAR) data were used with VV polari...
The class imbalance problem in automatic localization of the epileptogenic zone for epilepsy surgery: a systematic review.
Journal of neural engineering
Jun 26, 2025
Accurate localization of the epileptogenic zone (EZ) is crucial for epilepsy surgery, but the class imbalance of epileptogenic vs. non-epileptogenic electrode contacts in intracranial electroencephalography (iEEG) data poses significant challenges fo...
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