AI Medical Compendium

A three-dimensional skin-conformal hybrid electrode system for burden-free sEMG monitoring during exercises.

Biosensors & bioelectronics Feb 6, 2026

High-fidelity surface electromyography (sEMG) acquisition under dynamic conditions is critical for rehabilitation, sports monitoring, and human-machine interaction. Conventional electrodes often suffer from poor compliance, weak adhesion, and unstabl... read more

More Accurate Binding Affinity Prediction Using Protein Homology and Ligand-Based Transfer Learning.

Journal of chemical information and modeling Feb 6, 2026

Accurate and rapid prediction of protein-ligand binding affinities is critical for drug discovery, particularly when evaluating large chemical libraries or new drug molecules from high-throughput generative models. We present UCBbind, a hybrid framew... read more

Knowledge, Awareness and Perception of Artificial Intelligence (AI) - driven Prosthodontics in Jordan: A Cross-sectional Study.

The International journal of prosthodontics Feb 6, 2026

PURPOSE: Artificial intelligence (AI) is transforming modern dentistry, particularly in prosthodontics. However, evidence regarding AI integration among dental professionals in Jordan remains limited, while insights into educational and clinical gaps... read more

Ambient AI Documentation and Patient Satisfaction in Outpatient Care: Retrospective Pilot Study.

JMIR AI Feb 6, 2026

BACKGROUND: Patient experience is a critical consideration for any health care institution. Leveraging artificial intelligence (AI) to improve health care delivery has rapidly become an institutional priority across the United States. Ambient AI docu... read more

Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models.

JMIR diabetes Feb 6, 2026

BACKGROUND: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although advances in machine learning (ML) may enhance predictive capabilities compared to traditional stati... read more

Artificial intelligence-powered analysis of operating room turnover: impact of instrument burden.

Journal of neurosurgery Feb 6, 2026

OBJECTIVE: Improved operating room (OR) efficiency provides greater patient throughput, reduced costs, and maximal patient care. The aim of this study was to quantify and compare OR turnover efficiency across neurosurgical and otorhinolaryngology (EN... read more

Chemistry-Structure Dual-Perception Large Language Models: Advancing Molecular Property Prediction for Precise Disease Treatment.

IEEE journal of biomedical and health informatics Feb 6, 2026

Accurate prediction of drug molecular properties is crucial for precision drug discovery, which is closely related to precise disease diagnosis. Understanding the physicochemical properties, biological activities, and mechanisms of action of molecule... read more

HEQP: A Hypergraph Neural Network-Based Evolutionary Method for Large-Scale QCQPs.

IEEE transactions on cybernetics Feb 6, 2026

Machine learning-based optimization frameworks have attracted increasing attention for accelerating the solution of large-scale quadratically constrained quadratic programs (QCQPs) by exploiting shared problem structure across instances. However, exi... read more

Next-Gen Digital Predistortion From Hardware Acceleration of Neural Networks: Trends, Challenges, and Future.

IEEE transactions on neural networks and learning systems Feb 6, 2026

The computational demands of next-generation (Next-Gen) communication systems pose major challenges for real-time signal processing, particularly in digital predistortion (DPD), which is essential for linearizing power amplifier (PA) nonlinearities. ... read more

ASIL: Augmented Structural Information Learning for Deep Graph Clustering in Hyperbolic Space.

IEEE transactions on pattern analysis and machine intelligence Feb 6, 2026

Graph clustering is a longstanding topic in machine learning. In recent years, deep learning methods have achieved encouraging results, but they still require predefined cluster numbers $K$, and typically struggle with imbalanced graphs, especially i... read more

Artificial Intelligence Medical Compendium