Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 47,971 to 47,980 of 224,199 articles

Hand-gesture recognition using self-powered and single-electrode motion sensors fabricated with InN nanowires.

Materials horizons Feb 23, 2026
The ability to accurately monitor human motions such as hand-gestures is essential for establishing human-machine interface (HMI) systems for application in cutting-edge technologies such as robotics, artificial intelligence, and the internet of thin... read more 

From muscle to motion: GaIn nanoparticle-TPU core/shell mesh electrodes for intelligent prosthesis.

Materials horizons Feb 23, 2026
Electromyography (EMG) electrodes are critical for detecting and interpreting muscle activity, which is essential for operating prosthetic devices and wearable robots. Traditional EMG electrodes, however, often face limitations such as being uncomfor... read more 

Is the FDA regulation of cardiology AI devices supporting cardiovascular innovation: a scoping review.

Heart (British Cardiac Society) Feb 23, 2026
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have shown immense potential in cardiology, leveraging data-driven insights to enhance diagnosis, treatment planning and patient care. This study presents a comprehensive evaluation o... read more 

An snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging

bioRxiv Feb 23, 2026
Although multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us to identify potential age-associated genes directly. However, most existing transcriptomic clocks mo... read more 
genomics

Stabilization of recurrent neural networks through divisive normalization

bioRxiv Feb 23, 2026
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are sensitive t... read more 
neuroscience

Retrospective evaluation of human genetic evidence for clinical trial success using Mendelian randomization and machine learning

medRxiv Feb 23, 2026
Human genetics has become a cornerstone of drug target discovery, yet the value of Mendelian randomization (MR) for predicting clinical success remains uncertain. Here, we systematically evaluated MR across 11,482 target-indication pairs with documen... read more 
pharmacology and therapeutics

Smart stethoscope for cardiac auscultation in general practice: a prospective feasibility study of AI-assisted detection of atrial fibrillation, heart failure, and valvular heart disease

medRxiv Feb 23, 2026
Objectives: Artificial intelligence (AI) enabled digital stethoscopes combine phonocardiography and electrocardiography to support detection of cardiac rhythm and structural abnormalities. This study evaluated the feasibility and exploratory diagnost... read more 
primary care research

Anatomical Accuracy of Generative AI for Congenital Heart Disease Illustrations: Gemini NanoBanana Versus ChatGPT Models in a Blinded Comparative Study

medRxiv Feb 23, 2026
Background Generative artificial intelligence (AI) systems are increasingly used to produce medical illustrations for education; however, their anatomical accuracy in complex domains such as congenital heart disease (CHD) remains insufficiently valid... read more 
cardiovascular medicine

Genomic Evolution of SARS-CoV-2 Delta Variants Pre- and Post-Omicron Emergence using Alignment-free Machine Learning models

bioRxiv Feb 23, 2026
The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutations, underwent further genomic changes following the emergence of the Omicron variant (B.1.1.529). Th... read more 
genomics

Comprehensive top-down mass spectral repository enables pan-dataset analysis and top-down spectral prediction

bioRxiv Feb 23, 2026
Mass spectral libraries have become essential resources for training deep learning (DL) models for spectral prediction and de novo sequencing in bottom-up mass spectrometry (BU-MS). Compared with BU-MS, top-down MS (TD-MS) offers unique advantages fo... read more 
bioinformatics
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