AI Medical Compendium

The 3-Body Problem: How Astrocytes May Govern Plasticity.

The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry May 25, 2026

Learning and memory were long thought to be the domains of neurons and neural networks, but recent work across brain systems has established that astrocytes play a role in synaptic plasticity and information storage. However, it remains unclear what ... read more

A narrative review of the role of AI and machine learning in enhancing cauda equina syndrome diagnosis.

British journal of neurosurgery May 25, 2026

INTRODUCTION: Cauda Equina Syndrome (CES) is a neurological emergency requiring rapid diagnosis. Traditional diagnostic methods face challenges due to variable presentations. This review evaluates the clinical performance, limitations, and validation... read more

Generating Labeled Low-Heterogeneity Transcriptomes Using CRISPRa and CRISPRi Can Improve Phenotype Prediction by Deep Learning.

ACS synthetic biology May 25, 2026

The development of deep learning (DL) methods in biology holds great promise for fundamental knowledge, biomedicine, and agriculture. The most global challenge in this area is the development of models that use omics data to predict the complex pheno... read more

Overcoming LPS-mediated resistance in gram-negative pathogens: a review of LL-37 analogs and computational design strategies.

Archives of microbiology May 25, 2026

The increasing incidence of antimicrobial resistance (AMR) in Gram-negative bacteria has become a significant global health issue, driven primarily by the structural and adaptive characteristics of lipopolysaccharide (LPS) in the outer membrane. As a... read more

Environmental geochemistry and quality assessment of springs water in the Sikkim Himalaya: an entropy-weighted & machine learning approach.

Environmental geochemistry and health May 25, 2026

Himalayan rivers are crucial for freshwater supply, ecosystem services, and livelihoods across their course from mountains to floodplains, but climate change, human activities, and geological factors are increasingly degrading water quality. Given th... read more

Unsupervised anomaly detection for longitudinal comparison in whole-body PET/CT images.

International journal of computer assisted radiology and surgery May 25, 2026

PURPOSE: This study investigates the utility of unsupervised anomaly detection for longitudinal comparison of whole-body 18F-fluorodeoxyglucose (FDG)-PET/CT, which (1) reduces false-positive findings compared with subtraction-based methods and (2) en... read more

Digital Pathology in Head and Neck Squamous Cell Carcinoma: Translational Advances and Clinical Integration for Pathologists, Oncologists, and Surgeons.

Head and neck pathology May 25, 2026

PURPOSE: Artificial intelligence (AI)-enabled digital pathology has advanced rapidly in head and neck squamous cell carcinoma (HNSCC), but its readiness for clinical implementation remains uncertain. This review evaluates the translational maturity o... read more

Evaluating artificial intelligence-generated synthesized mammography as a standalone alternative to digital mammography with or without tomosynthesis.

Japanese journal of radiology May 25, 2026

PURPOSE: To evaluate whether standalone synthesized mammography (SM) can maintain or improve diagnostic accuracy while reducing reading time and radiation dose, compared to digital breast tomosynthesis (DBT) with digital mammography (DM) or DM alone.... read more

Integrative transcriptomic and single-cell analysis reveals metabolic reprogramming and hexosamine biosynthesis-mediated tumor microenvironment remodeling in prostate cancer.

Discover oncology May 25, 2026

BACKGROUND: Prostate cancer is one of the most common malignancies in men and exhibits substantial clinical heterogeneity. A considerable proportion of patients experience biochemical recurrence after primary treatment, and metabolic reprogramming ha... read more

Optimizing Deep Learning for Renal Mass Characterization in Challenging Cases: A Comparative Study of Spatial-Input Strategies and a Validated ROI-Only DLR Nomogram.

Annals of surgical oncology May 25, 2026

PURPOSE: Our purpose was to develop and validate an integrated clinical deep learning radiomics (DLR) nomogram for differentiation of fat-poor angiomyolipoma (fp-AML) from clear-cell renal cell carcinoma (ccRCC) in diagnostically challenging cases an... read more

Artificial Intelligence Medical Compendium