Artificial Intelligence Medical Compendium

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

Showing 36,951 to 36,960 of 223,469 articles

Machine Learning-Assisted Concentration-Independent Recognition of Neonicotinoids Based on Multienzyme-like Activities of FeCu Dual-Atom Nanozyme.

ACS applied materials & interfaces Apr 1, 2026
Residues of neonicotinoid insecticides (NEOs) pose serious threats to ecological systems and human health. Conventional nanozyme sensors often suffer from limited catalytic diversity and concentration-dependent response mechanisms, which lead to sign... read more 

Machine learning with temporal control designs for testing rhythmic specificity in chronobiology: A multivariate framework proposal for distinguishing genuine biological rhythms from temporal artifacts.

Chronobiology international Apr 1, 2026
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Isotropic and Strain-Insensitive Cellulosic Triboelectric Materials Enabled by the Hofmeister Effect.

Nano letters Apr 1, 2026
Achieving high-fidelity tactile sensing under dynamic deformation is a key bottleneck for the practical application of flexible electronics. However, conventional sensing materials face mechanical mismatch with biological tissues and signal distortio... read more 

AI-Powered Clinical Decision Support in Dentistry: Comparative Evaluation of Large Language Models for Oral Medicine and Periodontal Diagnosis.

Medical science monitor : international medical journal of experimental and clinical research Apr 1, 2026
BACKGROUND This study evaluates the diagnostic performance of 3 prominent artificial intelligence (AI)-powered large language models (LLMs) - ChatGPT, Copilot, and Gemini - as AI assistants for the diagnosis of oral lesions and periodontal conditions... read more 

LDIE-FDNet: Lightweight dynamic image enhancement-enabled real-time fatigue driving detection network.

PloS one Apr 1, 2026
Aiming at the imbalance between accuracy and real-time of existing fatigue driving detection models, and the accuracy is lower in low illumination, an LDIE-FDNet (Lightweight Dynamic Image Enhancement-Enabled Real-time Fatigue Driving Detection Netwo... read more 

A Bi-lingual chatbot implementation for pandemic response using the transformer-based approach.

PLOS digital health Apr 1, 2026
The COVID-19 pandemic highlighted the critical need for timely and accurate information in effectively managing pandemics. The proliferation of misinformation on public media platforms complicated the management of the pandemic, necessitating a large... read more 

Predictive modeling of gene expression and localization of DNA binding site using deep convolutional neural networks.

PLoS computational biology Apr 1, 2026
Despite the sequencing revolution, large swaths of the genomes sequenced to date lack any information about the arrangement of transcription factor binding sites on regulatory DNA. Massively Parallel Reporter Assays (MPRAs) have the potential to dram... read more 

Interpretable machine-learning prediction of household risk of trachoma and spatial hotspot mapping in Ethiopia.

Transactions of the Royal Society of Tropical Medicine and Hygiene Apr 1, 2026
BACKGROUND: Active trachoma remains above elimination thresholds in Ethiopia, yet tools for fine-scale targeting are limited. We developed and internally validated an interpretable machine-learning model to predict household-level risk of trachomatou... read more 

Machine learning-based ground motion simulation for seismic hazard assessment of critical water infrastructure in Azerbaijan (Case study: Major Shamkir water reservoir).

PloS one Apr 1, 2026
This study focuses on simulating ground motion for the Shamkir Water Reservoir area in Azerbaijan using machine learning algorithms to enhance regional seismic hazard assessments. Given the reservoir's location in a seismically active zone, potential... read more 

DEF-Net: A dual-modal feature enhancement and fusion network for infrared and visible object detection.

PloS one Apr 1, 2026
Infrared-visible object detection in complex dynamic environments often suffers from weak feature representation and underutilized cross-modal complementarity, leading to missed and false detections. To address these issues, we propose a Dual-modal E... read more 
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