Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1 to 10 of 200,346 articles

Single-cell transcriptomics and machine learning unveil liquid-liquid phase separation-related biomarkers in HPV-positive cervical cancer.

Infectious agents and cancer Jun 6, 2026
BACKGROUND: Liquid-liquid phase separation (LLPS) dysregulation is a key driver of oncogenesis, yet its specific role in HPV-positive cervical cancer remains undefined. We hypothesized that HPV-positive tumors exploit distinct LLPS mechanisms to evad... read more 

Mitigating hallucinations in healthcare AI: a systematic review of evidence-based strategies.

BMC health services research Jun 6, 2026
BACKGROUND: Large language models (LLMs) are increasingly integrated into healthcare applications, but their tendency to generate hallucinations-factually incorrect yet plausible outputs-poses risks to safety and trust. In clinical settings, these fa... read more 

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

Cancer immunology, immunotherapy : CII Jun 6, 2026
BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment options for resectable non-small cell lung cancer (NSCLC). However, clinical benefit varies across subpopulations, and standard linear models cannot f... read more 

CREP: Cis-Regulatory Element Predictor Based on Fine-Tuned Enformer

bioRxiv Jun 7, 2026
A substantial fraction of disease-associated genetic variants reside in non-coding regions of the genome, where they act by perturbing cis-regulatory elements (CREs) such as enhancers, promoters, and insulators. While recent sequence-based deep learn... read more 
bioinformatics

BacteReason: A Reasoning Model for Antimicrobial Resistance Prediction

bioRxiv Jun 7, 2026
The rapid global spread of antimicrobial resistance (AMR) has placed unprecedented pressure on clinical decision-making. Machine learning predictors of antibiotic susceptibility exist, but their lack of mechanistic grounding limits credibility. We pr... read more 
bioinformatics

Top Model Decision Tree: Selecting Segmentation Models for Reliable Quantitative Analysis in Low- and Ultralow-Dose CryoEM

bioRxiv Jun 6, 2026
Deep learning neural networks provide a powerful approach for segmenting low-contrast cryogenic electron microscopy (cryoEM) images. However, model performance can vary significantly across imaging conditions and may hinder downstream quantitative an... read more 
microbiology

Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders

bioRxiv Jun 6, 2026
Light microscopy of tissue sections stained with hematoxylin and eosin (H&E) has been the foundation of histopathology for over 150 years and remains essential for diagnosis and research. The development of high-plex spatial profiling approaches able... read more 
bioinformatics

Single-Cell Multi-Omics Dissection of Malignant Evolutionary Mechanisms and Construction of a Prognostic Model for Clear Cell Renal Cell Carcinoma

bioRxiv Jun 6, 2026
Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studies characterizing these transitions remain limited. We integrated scRNA-seq and scATAC-seq data acro... read more 
bioinformatics

TetraFuse: A Synergistic Four-Dimensional Dynamic Fusion Framework for Efficient and Robust Medical Image Classification

bioRxiv Jun 6, 2026
Accurate and robust classification of medical pathology images is pivotal for computer-aided diagnosis. However, the deployment of deep learning models in high-throughput clinical screening faces a fundamental challenge: the trade-off between diagnos... read more 
bioinformatics

Automated Retinal Dysplasia Segmentation in Mouse Optical Coherence Tomography Scans Using a UNet-Based model

bioRxiv Jun 6, 2026
Optical coherence tomography (OCT) is the state-of-the-art non-invasive imaging technique for preclinical retinopathy studies. However, manual pathology annotations in mouse OCT scans are labour-intensive and susceptible to inter-rater variability. T... read more 
bioinformatics
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