Artificial Intelligence Medical Compendium

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

Showing 3,041 to 3,050 of 202,937 articles

Exploring students' emotional experiences and responses to AI tutors and their limitations in higher education: a Self-Determination Theory (SDT) perspective.

BMC psychology
BACKGROUND: A growing body of research underscores the role of artificial intelligence (AI) technologies in second language (L2) education. However, the emotional side of adopting AI tutors in the English as a foreign language (EFL) context has recei... read more 

An interpretable machine learning model for preoperative risk stratification in paediatric congenital heart disease surgery: a retrospective cohort study.

Journal of cardiothoracic surgery
BACKGROUND: Congenital heart disease (CHD), one of the most common birth defects, poses challenges to preoperative risk stratification due to its anatomical complexity and developmental vulnerability. Existing tools inadequately predict critical outc... read more 

Benchmarking reveals the superiority of nucleic acid foundation models in predicting lncRNA coding potential.

Genome biology
BACKGROUND: A subset of long noncoding RNAs (lncRNAs) contains short open reading frames and can encode functional micropeptides. However, identifying these coding lncRNAs (codlncRNAs) remains challenging due to weak coding signals, short peptide pro... read more 

AI in esophageal cancer: advances, barriers to clinical translation, and perspectives for digital health.

Journal of translational medicine
BACKGROUND: Esophageal cancer (EC) remains one of the leading causes of cancer-related mortality worldwide. Accurate staging, treatment planning, and prognostic assessment are essential for improving clinical management and patient outcomes. In recen... read more 

SR-FSL: Sample reconstruction enhanced few-shot learning for real-time motor unit identification from surface electromyogram.

Journal of neuroengineering and rehabilitation
BACKGROUND: Deep learning (DL) methods have demonstrated promising performance in online motor unit (MU) identification from high-density surface electromyogram (HD-sEMG). However, its dependency on larger amounts of data limits practicability. METHO... read more 

Stem cell research and regenerative medicine: meeting report from the Royan International Stem Cell Congress 2025.

Journal of biological engineering
The 21st Royan International Stem Cell Congress (3-5 September 2025, Tehran, Iran) convened the global stem cell community to assess the accelerating translation of regenerative medicine from bench to bedside. Over three days, 10 thematic sessions, s... read more 

A systemic immune signature stratifies early-stage breast cancer patients and reveals soluble IL-2RA and PD-1 as potential independent prognostic biomarkers.

Breast cancer research : BCR
BACKGROUND: Breast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. Systemic immune dysregulation is increasingly recognized as a critical component of BC pathophysiology. Therefore, the characte... read more 

Deep learning in image forgery: A systematic review for risk of bias (RoB).

Journal of forensic sciences
Image forgery (IF) is a critical issue that can lead to the misinterpretation of visual information. Conventional strategies for IF detection are primarily manual feature-based and therefore require further analysis. Artificial intelligence (AI) has ... read more 

Predicting Enhancer-Promoter Interactions Using a Stacking-Based Ensemble Strategy.

Bioinformatics (Oxford, England)
MOTIVATION: Enhancer-promoter interactions (EPIs) are essential for gene regulation and disease progression. Recent studies have shown that distal enhancers can regulate target genes through interactions with nearby promoters, providing important ins... read more 

A unified multimodal model for generalizable zero-shot and supervised protein function prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Predicting protein function is a fundamental and challenging task that requires integrating diverse biological data modalities to capture complex functional relationships. Traditional machine learning methods often rely on single modaliti... read more