AI Medical Compendium

Atrial Fibrillation Ablation Using 3D Artificial Intelligence Module Integration with Intracardiac Echocardiography.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Jan 16, 2026

BACKGROUND: Intracardiac echocardiography (ICE)-based electroanatomical mapping (EAM) improves procedural efficiency and safety in atrial fibrillation (AF) ablation and remains the standard of care. The CARTOSOUND FAM (AI FAM) module uses a deep-lear... read more

Neurotransmission-modulated whole-brain computation captures full task repertoire.

Cell reports Jan 16, 2026

An important unsolved problem is how the brain survives in a complex world by performing a rich repertoire of computation on a minimal energy budget. Despite using a seemingly fixed architecture, the brain performs much better than current generation... read more

Intelligent control for food waste composting using observation-assessment-decision-action cycles: From technical landscape to economic stability analysis.

Journal of environmental management Jan 16, 2026

Intelligent control systems (ICS) based on sensor technology and machine learning (ML) can improve the inefficiency and instability of traditional food waste (FW) composting processes, yet quantitative, deployment-oriented techno-economic assessments... read more

Meteorological associations with out-of-hospital cardiac arrest: A national population-based time-series analysis.

Public health Jan 16, 2026

OBJECTIVES: Meteorological factors may influence cardiovascular emergency incidence, but comprehensive national evidence for out-of-hospital cardiac arrest (OHCA) associations remains limited. We investigated meteorological associations with OHCA occ... read more

Predictive modeling and spatiotemporal analysis of TB in Argentina: Advancing control efforts through machine learning.

Public health Jan 16, 2026

OBJECTIVES: To improve prediction and understanding of TB dynamics in Argentina, identifying key risk factors and high-incidence areas to inform surveillance and public health control strategies. STUDY DESIGN: Retrospective observational study. METHO... read more

Impact of a new deep-learning image reconstruction algorithm on potential dose reduction and quality of chest CT images: a phantom study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jan 16, 2026

PURPOSE: To evaluate the impact of a new deep-learning image reconstruction (DLR) algorithm on image quality and potential dose reduction compared with a hybrid iterative reconstruction (IR) algorithm under chest CT conditions. MATERIALS AND METHODS:... read more

Machine learning guided structural dynamics identifies translation elongation factor 1 (EEF1A1) as an immunological biomarker and marine natural products as therapeutic leads for rheumatoid arthritis with major depressive disorder.

Computers in biology and medicine Jan 16, 2026

Rheumatoid arthritis (RA) is a systemic autoimmune disease that predominantly affects synovial joints, especially those of the hands, elbows, wrists, knees, and shoulders. RA frequently co-occurs with major depressive disorder (MDD), amplifying disea... read more

IntNet: Lightweight yet high-performance deep learning system for intuitive radar patterns analysis and human fall detection.

Computers in biology and medicine Jan 16, 2026

The growing trend of solitary living among the elderly and young, coupled with the high risk of falls leading to injuries and death, highlights the need for fall monitoring systems. Emphasizing individuals' privacy and comfort, these systems should r... read more

DrowsyDG-Phys: Generalizable driver drowsiness estimation in conditional automated vehicles using physiological signals.

Accident; analysis and prevention Jan 16, 2026

Driver drowsiness is one of the leading causes of crashes, injuries, and fatalities on the road. Traditional drowsiness detection models relied on manually extracted physiological features processed through machine learning algorithms. However, these... read more

A graph-based spatio-temporal framework for predicting safety-critical pedestrian-vehicle interactions at unsignalized crosswalks.