AI Medical Compendium

Ontology-Enhanced Deep Learning for Mechanistic Prediction of Drug-Drug Interactions: A Clinically Interpretable Framework.

Journal of clinical pharmacology Jun 1, 2026

Drug-drug interactions (DDIs) have critical impacts on patient safety and healthcare efficiency because of their significant contributions to adverse drug reactions. Accurately predicting DDIs and their biological mechanisms is therefore essential, y... read more

Integration of Raman Spectroscopy and Metabolomics for Early Breast Cancer Detection and Classification.

Cancer medicine Jun 1, 2026

Breast cancer, now the fourth leading cause of cancer-related mortality worldwide, necessitates early detection for improved clinical outcomes. Conventional histopathology, though widely used, is invasive and subjective, limiting its utility in early... read more

Machine Learning and Clustering Analysis of Class II and III Malocclusions.

Clinical and experimental dental research Jun 1, 2026

OBJECTIVES: This prospective observational study aims to accurately classify individuals as skeletal class II/III by applying several machine-learning algorithms. Furthermore, using the k-means clustering analysis deepened our understanding of the ch... read more

Comorbidities for Predicting Progression Independent of Relapse Activity in Multiple Sclerosis Treated With B-Cell Depletion.

European journal of neurology Jun 1, 2026

BACKGROUND: Progression independent of relapse activity (PIRA) has been shown to account for a majority of the disability accumulation in relapsing-remitting multiple sclerosis (RRMS) patients treated with disease-modifying therapies. While comorbidi... read more

Artificial Intelligence-Enhanced Implantable Loop Recorders in Pediatric Patients: Effects on Device Performance and Clinical Workflow in a Single-Center Experience.

Journal of cardiovascular electrophysiology Jun 1, 2026

INTRODUCTION: Artificial intelligence (AI)-based algorithms have been developed to reduce alert burden in patients with implantable loop recorders (ILRs), but their performance in pediatric populations has not been previously evaluated. METHODS: We r... read more

[A nomogram combining ultrasound radiomics and clinical features for predicting pathological invasiveness of papillary thyroid carcinoma].

Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences Jun 1, 2026

OBJECTIVES: To develop a nomogram model combining ultrasound radiomics and clinical features and to evaluate its predictive value for pathological invasiveness of papillary thyroid carcinoma (PTC). METHODS: This study included 224 patients diagnosed ... read more

Computational Quantification of Peristalsis in Preclinical Mouse Models Using Smartphone Videography.

Neurogastroenterology and motility Jun 1, 2026

BACKGROUND: A number of diseases and medical interventions affect gastrointestinal motility. However, quantitative methods for measuring effects on peristalsis in live animals are uncommon, cumbersome, and lack standardization. METHODS: Here we prese... read more

Generative Artificial Intelligence Optimization of Albumin Binders: Coumarin and Fatty Acid Derivatives.

Journal of chemical information and modeling Jun 1, 2026

Previously, we reported a dual combination based on 4-hydroxycoumarin and dodecanedioic acid that could synergistically bind to human serum albumin (HSA). However, optimizing this combination remains challenging and could often be guided by empirical... read more

Artificial Intelligence Methods in Early Detection of Autism Spectrum Disorder: A DSM-5 Criterion-Based Systematic Review.

Autism research : official journal of the International Society for Autism Research Jun 1, 2026

Can Artificial Intelligence (AI) revolutionize early detection of Autism Spectrum Disorder (ASD) by offering a more objective alternative to the subjective behavioral assessments? This systematic review evaluates AI-based methods for early ASD detect... read more

Predictive and interactive roles of motivation and situational learning activities on emotional and cognitive engagement.

The British journal of educational psychology Jun 1, 2026

BACKGROUND: Emotions and cognitions are important factors of learning engagement. While extensive research focuses on in-class activity, there is a gap in understanding engagement in out-of-class study contexts, particularly the interplay between mot... read more

Artificial Intelligence Medical Compendium