Artificial Intelligence Medical Compendium

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

Showing 57,431 to 57,440 of 227,388 articles

Minimally Invasive / Robotic Surgery for Hepatobiliary Cancer.

Surgical oncology clinics of North America Jan 29, 2026
Minimally invasive liver surgery (MILS), including laparoscopic liver surgery and robotic liver surgery, has come a long way in the management of primary liver tumors. This article summarizes current evidence and institutional experience regarding th... read more 

Machine Learning-Based Prediction of Postoperative Refraction in Cataract Surgery: A Stacking Ensemble Approach

medRxiv Jan 29, 2026
Background: Achieving precise postoperative refractive outcomes remains a significant challenge in cataract surgery. While advanced intraocular lens (IOL) power calculation formulas exist, they are constrained by their singular algorithmic structures... read more 
ophthalmology

Medical Students' Use of Large Language Models: A National Survey

medRxiv Jan 29, 2026
Background: Large language models (LLMs) are increasingly embedded in medical education and clinical care settings, yet limited empirical data describe medical students in Canada's use and perceptions of these tools. We aimed to characterize student ... read more 
medical education

MedEvalArena: A Self-Generated, Peer-Judged Benchmark for Medical Reasoning

medRxiv Jan 29, 2026
Large Language Models (LLMs) demonstrate strong performance at medical specialty board multiple-choice question (MCQ) answering, however, underperform in more complex medical reasoning scenarios. This gap indicates a need for improving both LLM medic... read more 
health informatics

Persistent Proxy Discrimination in HIV Testing Prediction Models: A National Fairness Audit of 386,775 US Adults

medRxiv Jan 29, 2026
Background: Human immunodeficiency virus (HIV) disproportionately affects marginalized communities in the United States, with Black Americans comprising 42% of new diagnoses despite representing 13% of the population. Machine learning (ML) prediction... read more 
health informatics

Multi-omic deep learning identifies exercise-responsive ageing pathways in humans

medRxiv Jan 29, 2026
Genome-wide association studies of physical activity traits have mapped numerous loci, yet the molecular mechanisms through which exercise influences human biology remain poorly defined. Mechanistic progress has been limited by heritability-dominated... read more 
sports medicine

A neural network model delivers a highly prognostic protein signature in cancer stem cells that identifies relapse in stage III colorectal cancer patients.

bioRxiv Jan 29, 2026
Background Stage III colorectal cancer poses a significant threat of metastasis development, as tumour resection and adjuvant chemotherapy do not guarantee prolonged disease-free survival. Objective The spatial, quantitative, and qualitative characte... read more 
cancer biology

Machine Learning Ensemble Reveals Distinct Molecular Pathways of Retinal Damage in Spaceflown Mice

bioRxiv Jan 29, 2026
Spaceflight-associated neuro-ocular syndrome (SANS) threatens astronaut health during long-duration missions, yet its molecular pathology remains unclear. Two physiological pathways exist: one attributes SANS to microgravity-induced cephalic fluid sh... read more 
bioinformatics

Circuit-Specific Resting-State fMRI Signatures for Stratifying First-Episode Major Depressive Disorder and Predicting Recurrence Risk

bioRxiv Jan 29, 2026
Background: Depression is biologically heterogeneous, and first-episode depression (FED) carries a high risk of recurrence that is poorly captured by symptom-based assessment. Early identification of patients likely to relapse, as well as reliable id... read more 
neuroscience

A human-in-the-loop explanation framework for morphologically transparent AI predictions from whole-slide images

bioRxiv Jan 29, 2026
Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as "black boxes", lacking transparency about whether and which histomorphological patterns drive their predictions, hinderi... read more 
pathology
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