AI Medical Compendium

Cluster analysis: an overview of traditional and novel approaches for health researchers.

European journal of cardiovascular nursing May 26, 2026

Cluster analysis has gained increased importance with the rapid expansion of artificial intelligence (AI) and data-driven research. As a central method in unsupervised machine learning, it can reveal hidden patterns and identify homogenous subgroups ... read more

From gene discovery to synthetic biology: recent advances in the biosynthesis of oleanane-type pentacyclic triterpenoids.

Natural product reports May 26, 2026

Covering: 2010 to January 2026Oleanane-type pentacyclic triterpenoids (OPTs) represent a prominent class of plant-derived natural products, widely recognized for their potent pharmacological properties, including anticancer, anti-inflammatory, and an... read more

A Multistage Virtual Screening Strategy Integrating Molecular Similarity, Deep Learning Scoring, and Molecular Docking toward the Discovery of Novel LRRK2 Inhibitors.

Journal of chemical information and modeling May 26, 2026

Leucine-rich repeat kinase 2 (LRRK2) has emerged as an attractive molecular target for Parkinson's disease therapeutics. To discover novel and potent LRRK2 inhibitors, we employed an integrated virtual screening workflow comprising a similarity searc... read more

Bridging Hydrocarbon Thermodynamics and Electron-Density Isosurfaces with Explainable Machine Learning.

The journal of physical chemistry. A May 26, 2026

Key thermodynamic properties of hydrocarbons are essential for process design and for reliable thermodynamic modeling. Experimental measurements are often costly or unavailable for many compounds, and prediction models are rarely further updated and ... read more

Can machine learning identify inherited causes of thrombocytopenia? A feasibility study.

British journal of haematology May 26, 2026

Artificial intelligence models for predicting ASA physical status classification: a systematic review and meta-analysis.

Minerva anestesiologica May 26, 2026

BACKGROUND: The American Society of Anesthesiologists (ASA) physical status classification remains the cornerstone of preoperative risk assessment but is limited by its subjective nature and only moderate inter-rater reliability. Artificial intellige... read more

Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) May 26, 2026

Artificial intelligence (AI) is increasingly applied to biomedical research, but most current systems remain limited to specific tasks, data types, or biological scales. This makes it difficult to connect molecular alterations, organelle dysfunction,... read more

A study on a high efficiency phase organization segmentation model for SEM images based on deep learning.

Nanoscale May 26, 2026

Quantitative characterization and analysis of material microstructures play a crucial role in understanding material properties. Traditional U-Net architectures, however, are often vulnerable to noise and prone to overfitting when applied to small da... read more

Multidomain correlates of burnout: A population-based study using supervised machine learning.

Social psychiatry and psychiatric epidemiology May 26, 2026

PURPOSE: Burnout is a growing challenge for individuals and society and understanding risk factors is crucial to develop targeted prevention strategies. Thus, we aimed to determine whether and how burnout relates to different organisational factors, ... read more

Inter-rater reproducibility in medico-legal injury assessment: a pilot study with an exploratory comparison to a large language model.

International journal of legal medicine May 26, 2026

Reproducibility in medico-legal personal injury assessment should be regarded as a fundamental prerequisite for transparent and equitable compensation. However, inter-rater agreement is rarely examined and quantified, even within a single regulatory ... read more

Artificial Intelligence Medical Compendium