AI Medical Compendium

Machine Learning Accelerated Non-Adiabatic Molecular Dynamics Elucidates Local Polarization Effects on Non-radiative Recombination in Halide Perovskites.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) May 29, 2026

Non-radiative recombination is a critical factor limiting the optoelectronic performance of halide perovskites, yet how local polarization induced by charge redistribution regulates this process remains unclear. To gain deeper insight while reducing ... read more

How Advanced Artificial Intelligence Technologies Shape Drug-Drug and Drug-Target Interaction Modeling.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) May 29, 2026

Drug molecular interactions, including drug-drug interactions (DDIs) and drug-target interactions (DTIs), are critical for drug discovery and clinical safety, increasingly propelled by artificial intelligence (AI) technologies. Although previously tr... read more

Artificial Intelligence for Sleep Instability and Motor Phenotyping: Clinical Translation Beyond Sleep Staging.

Sleep May 29, 2026

Sleep medicine has rapidly adopted artificial intelligence, but most applications still prioritize automated sleep staging or single summary indices, limiting clinical translation when symptoms arise from within-stage dynamics. This review proposes a... read more

Harnessing and Suppressing Electron Spin-State Transitions: From Decoding to Rational Design of High-Performance Cathodes for Alkali-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany) May 29, 2026

The electron spin state of transition metal ions represents a fundamental quantum property that is increasingly recognized as a pivotal design dimension for tuning the performance of cathode materials in Li/Na/K‑ion batteries. This review begins by c... read more

Does Patient History Influence Capsular Contracture? An Exploratory Analysis with Machine Learning.

Aesthetic plastic surgery May 29, 2026

BACKGROUND: Capsular contracture (CC) is a frequent and distressing complication of breast augmentation and reconstruction. Although numerous patient-, surgical-, and implant-related risk factors have been proposed, reliable population-level predicto... read more

Evaluating cognitive biases in AI-assisted mammography interpretation: a simulation reader study of explainable AI across radiologist experience levels.

European radiology May 29, 2026

OBJECTIVES: To evaluate the impact of automation and anchoring bias in artificial intelligence (AI)-assisted mammography interpretation and to assess whether saliency-based explainable AI (XAI) mitigates these biases across radiologists of varying ex... read more

Machine Learning-Based Prediction Model for 30-Day Emergency Department Revisits in a Medically Underserved Tertiary Hospital: Formative Retrospective Cohort Study.

JMIR formative research May 29, 2026

BACKGROUND: Emergency department (ED) revisits are critical quality indicators, particularly in medically underserved areas, where traditional prediction tools show limited performance. Machine learning (ML) approaches may offer improved predictive p... read more

A macrophage-related efferocytosis-based two-gene prognostic model for acute myeloid leukemia identified by multi-omics and machine learning.

Annals of hematology May 29, 2026

Background Acute myeloid leukemia (AML) remains a lethal hematologic malignancy with high heterogeneity. Macrophage-mediated efferocytosis in the tumor microenvironment is implicated in immune suppression and disease progression. Methods We integrate... read more

An integrated computational-experimental approach identifies Malate Synthase G as therapeutic target to disrupt carbon metabolism in chronic Pseudomonas aeruginosa infection.

Functional & integrative genomics May 29, 2026

Pseudomonas aeruginosa is a leading cause of nosocomial infections, particularly in individuals with a compromised immune system. Due to its strong adaptive ability, P. aeruginosa tends to develop antibiotic resistance and establish chronic infection... read more

Turning failure into success: how artificial intelligence can help personalize therapies and re-use patient data.

Purinergic signalling May 29, 2026

Despite robust preclinical evidence, many clinical trials, including several that targeted the purinergic system, fail to demonstrate efficacy in humans. Failure may stem from inability to accurately identify patient subgroups responding similarly to... read more

Artificial Intelligence Medical Compendium