AI Medical Compendium

Gradient-informed neural networks: Embedding prior beliefs for learning in low-data scenarios.

Neural networks : the official journal of the International Neural Network Society Feb 2, 2026

We propose Gradient-Informed Neural Networks (gradinn s), a methodology that can be used to efficiently approximate a wide range of functions in low-data regimes, when only general prior beliefs are available, a condition that is often encountered in... read more

Explainable AI in Cardiology Diagnostics: A Systematic Review of Machine Learning, Meta-heuristic Optimization, and Clinical Text Mining for Coronary Artery Disease.

International journal of medical informatics Feb 2, 2026

BACKGROUND: This systematic review compiles evidence and examines how various artificial intelligence (AI) approaches, including machine learning (ML), natural language processing (NLP), meta-heuristic optimization, and explainable AI (XAI), are util... read more

A machine learning model for prediction of risk of dementia superimposed on delirium in intensive care patients.

Archives of gerontology and geriatrics Feb 2, 2026

BACKGROUND: The objective of this study was to construct a predictive model using multiple machine learning algorithms to predict the risk of dementia superimposed on delirium (DSD) in dementia patients in the ICU. METHODS: The data for this study we... read more

Bridging causality and deep learning for harmful algal bloom prediction.

Water research Feb 2, 2026

Accurate estimation of chlorophyll-a (Chl-a) is essential for monitoring harmful algal blooms (HABs), particularly in vulnerable coastal regions. However, most machine learning (ML) approaches rely on purely correlative patterns, often lacking causal... read more

Structure-missing graph-level clustering network.

Neural networks : the official journal of the International Neural Network Society Feb 2, 2026

Graph-level clustering aims to group graphs into distinct clusters based on shared structural characteristics or semantic similarities. However, existing graph-level clustering methods generally assume that the input graph structure is complete and o... read more

Resolving sequential electron-proton transfer kinetics for electrochemical CO2 reduction at the Cu(100)/H2O interface via a quantum-classical framework.

Chemical science Feb 2, 2026

Electron-transfer (ET) and proton-transfer (PT) events occurring at electrochemical interfaces ultimately dictate the efficiency of electrocatalytic energy conversion and chemical synthesis. Despite their significance, a unified theoretical descripti... read more

Open-surface digital ELISA enabled by magnetic trapping and deep learning for rapid and highly sensitive detection of African swine fever.

Biosensors & bioelectronics Feb 2, 2026

African swine fever (ASF), a highly fatal and contagious animal disease caused by ASF virus, leads to substantial economic losses. Early detection is critical, as the viral load is initially low, demanding highly sensitive detection of the viral p30 ... read more

Artificial intelligence in psychiatry: A global perspective on research status, trends and clinical applications.

Journal of psychiatric research Feb 2, 2026

Artificial intelligence is increasingly used in psychiatric research, yet progress in clinical use and equitable benefit remains uneven. We analyzed 2795 Web of Science publications on artificial intelligence in psychiatry using bibliometrics and BER... read more

Uncertainty in deep learning for EEG under dataset shifts.

Artificial intelligence in medicine Feb 2, 2026

As artificial intelligence (AI) is increasingly integrated into medical diagnostics, it is essential that predictive models provide not only accurate outputs but also reliable estimates of uncertainty. In clinical applications, where decisions have s... read more

Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.