AI Medical Compendium

RT2C: Predicting Time-to-New Caries with Structured Dental Data Using RNN.

Journal of dental research Jul 18, 2026

Dental caries is a highly prevalent chronic condition requiring accurate tools to identify at-risk patients and guide preventive care. Most existing caries risk models provide only binary predictions and overlook time-to-event information. Considerin... read more

Controllable Panoramic Radiograph Synthesis Using a Generative Model.

Journal of dental research Jul 18, 2026

Panoramic radiography (PR) is the one of the most widely prescribed diagnostic imaging modalities in dentistry. Achieving clinical-level automated interpretation of PR is critical for improving diagnostic efficiency, reducing radiologist workload, an... read more

Mapping Non-Homologous Pocket Compatibilities to Identify Hidden Drug-Target Relationships: A Pocket Hopping Framework.

Journal of medicinal chemistry Jul 18, 2026

Predicting small molecule-protein interactions across nonhomologous proteins remains challenging because shared ligand recognition is often not evident from sequence, fold, or pocket similarity. Here, we introduce pocket hopping, a machine-learning f... read more

Interpretable Machine Learning Framework for Gas Adsorption Prediction and Screening on Transition Metal Dichalcogenides.

Langmuir : the ACS journal of surfaces and colloids Jul 18, 2026

Two-dimensional transition metal dichalcogenides (TMDs) are promising gas-sensing materials, but adsorption behavior across doped host-dopant-gas spaces remains difficult to predict and interpret. Here, we develop a descriptor-informed machine-learni... read more

Random Forest Modeling to Predict Small Molecule Accumulation in Gram-Negative Bacteria.

ACS infectious diseases Jul 18, 2026

Despite extensive efforts over the past ∼60 years to discover new classes of Gram-negative-active antibiotics, the development pipeline remains relatively dry. These failures can be largely ascribed to the complexity of the Gram-negative membranes an... read more

Investigating the mechanisms of malignant progression in colorectal cancer using weighted gene co-expression network analysis and machine learning.

Journal of molecular histology Jul 18, 2026

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Understanding the complex molecular networks that underlie this aggressive behavior is critical for developing novel diagnostic and therapeutic strategies. This st... read more

Age-Related Brain Atrophy Mediates a Composite Outcome of One-Year Ischemic Stroke Recurrence and All-Cause Mortality Through YKL-40-Related Inflammatory Pathways: A Structural Equation Model.

Translational stroke research Jul 18, 2026

Chronological age is a strong predictor of poor outcomes after ischemic stroke but may not fully capture underlying biological vulnerability. This study investigated whether age-related brain atrophy and plasma YKL-40, a marker of astroglial inflamma... read more

Predictive Modeling of Coronary Artery Disease Using Color Fundus Photography-Based Features of Retinal Vasculature.

Ophthalmology and therapy Jul 18, 2026

INTRODUCTION: Coronary artery disease (CAD) remains the leading cause of death and current screening methods are limited. Color fundus photography (CFP) has been explored in literature mostly on the basis of associations and exploratory deep learning... read more

Artificial Intelligence and Protein Design: A retrospective study on 20-year emerging trends and core research areas from bibliometric perspectives.

Probiotics and antimicrobial proteins Jul 18, 2026

Protein design has numerous applications in synthetic biology, drug discovery, and bioengineering. Recently, there has been a revolution in this field due to the emergence of artificial intelligence. At the forefront are deep learning models (DLMs). ... read more

Teaching in the trenches: adaptive strategies for clinical education in crowded emergency departments.

CJEM Jul 18, 2026

Emergency department crowding has become a pervasive global challenge that strains patient flow and compromises clinical learning environments. Traditional teaching approaches are often impracticable when patient volumes exceed system capacity and cl... read more

Artificial Intelligence Medical Compendium