AI Medical Compendium

TADynFed: Dynamic modality-adaptive federated learning with tissue-aware disentanglement for cross-disease analysis.

Artificial intelligence in medicine Feb 19, 2026

Federated learning (FL) enables collaborative medical image analysis across decentralized institutions while preserving data privacy. However, real-world deployment faces critical challenges: modality heterogeneity, where clients possess incomplete o... read more

Electroencephalography-Based Machine Learning Models for Predicting Ketogenic Diet Outcomes in Pediatric Drug-Resistant Epilepsy.

Pediatric neurology Feb 19, 2026

BACKGROUND: Ketogenic diet therapy (KDT) is an established treatment for drug-resistant epilepsy (DRE); however, methods for predicting its effectiveness remain underdeveloped. This study evaluated various machine learning (ML) models in predicting r... read more

Rapid geographical traceability and quality identification of black tea via integration of ambient mass spectrometry and machine learning.

Food research international (Ottawa, Ont.) Feb 19, 2026

Accurate geographical traceability and comprehensive adulteration assessment of black tea are essential for quality control and market regulation, but remain challenging due to subtle metabolic differences and complex adulteration practices. In this ... read more

Advanced Real-Time, Non-Destructive Spectral Fingerprinting for Early microbial Spoilage Detection: AI-Integrated Raman Biosensing Platform for Scalable Food Safety and Quality.

Food research international (Ottawa, Ont.) Feb 19, 2026

Food spoilage poses a global challenge, contributing to economic losses, food insecurity, and health risks from microbial contamination. Conventional detection methods are often destructive, time-consuming and ineffective at identifying early biochem... read more

NPHS2 Revisited Through 208 Cases and Podocin Complex Modeling.

Kidney international reports Feb 19, 2026

INTRODUCTION: Steroid-resistant nephrotic syndrome (SRNS) is the leading cause of chronic glomerular disease in individuals under 25 years of age. Biallelic variants in NPHS2, encoding podocin, are the most common monogenic etiology. Podocin homo-oli... read more

Multimodal graph fusion-based GCN for Alzheimer's disease diagnosis using fMRI and T1-weighted MRI.

Neural networks : the official journal of the International Neural Network Society Feb 19, 2026

Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by both structural atrophy and functional dysregulation in the brain, yet its early detection remains elusive. Although recent efforts have leveraged artificial intelligence ... read more

Assessing the Reliability of Large Language Models for Evaluation of Risk of Bias in Randomized Clinical Trials.

American journal of perinatology Feb 19, 2026

OBJECTIVE: Systematic reviews depend on rigorous risk-of-bias (RoB) assessments to ensure credibility, yet manual evaluation using the Cochrane RoB 2 tool is resource-intensive. While large language models (LLMs) offer potential for automation, their... read more

Human in the loop artificial intelligence in healthcare: applications, outcomes, and implementation challenges.

International journal of medical informatics Feb 19, 2026

BACKGROUND: The integration of artificial intelligence in healthcare has transformed clinical practice and research methodologies. However, concerns regarding algorithmic accountability, interpretability, and safety have necessitated human oversight ... read more

Utopian or dystopian? A mixed-methods study of nursing and midwifery students' perceptions of artificial intelligence and robot-assisted person-centred care in education.

Nurse education today Feb 19, 2026

BACKGROUND: The integration of artificial intelligence (AI) and robotic technologies into healthcare is increasing, making it important to understand how future professionals view these innovations. This study explored nursing and midwifery students'... read more

GSASN: a graph self-learning attention scores network for spatial modeling of network traffic matrix prediction.