Artificial Intelligence Medical Compendium

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

Showing 26,771 to 26,780 of 218,283 articles

MRDT-GAN: generative adversarial network with multi-scale residual dense transformer generator for low-dose CT denoising.

Physics in medicine and biology Apr 24, 2026
Objective.Low-dose computed tomography (LDCT) reduces radiation exposure but introduces noise and artifacts that degrade diagnostic quality. Existing deep learning-based denoising methods still face challenges such as over-smoothing, loss of fine str... read more 

MIMIC-IV-Phenotype-Atlas (MIPA) : A Publicly Available Dataset for EHR Phenotyping

medRxiv Apr 24, 2026
Introduction Secondary use of electronic health records (EHRs) often requires transforming raw clinical information into research-grade data. A central step in this process is EHR phenotyping - the identification of patient cohorts defined by specifi... read more 
health informatics

A Systematic Exploration of LLM Behavior for EHR phenotyping

medRxiv Apr 24, 2026
Background Electronic health record (EHR) phenotyping underpins observational research, cohort discovery, and clinical trial screening. Large language models (LLMs) offer new capabilities for extracting phenotypes from unstructured text, but their pe... read more 
health informatics

Deep Learning Reveals the Modular Genetic Architecture of Cardiovascular Aging

medRxiv Apr 24, 2026
Chronological age is a potent determinant of clinical events, but it is conventionally treated as a linear function of time rather than a dynamic process shaped by genetics and tissue-specific senescence. Deep learning models derived from cardiovascu... read more 
cardiovascular medicine

Analysis and Mitigation of Equipment-induced Shortcuts in AI Models for Laparoscopic Cholecystectomy

medRxiv Apr 24, 2026
Machine learning models have seen a lot of success in medical image segmentation domain. However, one of the challenges that they face are confounders or shortcuts: spurious correlations or biases in the training data that affect the resulting models... read more 
surgery

Comparison of the Expert Guidelines With Artificial Intelligence-Driven Echocardiographic Assessment of Diastolic Function

medRxiv Apr 24, 2026
Backgound: Accurate assessment of diastolic function and left ventricular (LV) filling pressure is central to heart failure diagnosis and risk stratification. Contemporary guideline algorithms rely on complex parameters that are not consistently avai... read more 
cardiovascular medicine

Large language models and retrieval augmented generation for complex clinical codelists: evaluating performance and assessing failure modes

medRxiv Apr 24, 2026
Objectives: Large language models (LLMs) have shown promise in creating clinical codelists for research purposes, a time-consuming task requiring expert domain knowledge. Here, we evaluate the performance and assess failure modes of a retrieval augme... read more 
health informatics

Generalizing intensive care AI across time scales in resource-limited settings

medRxiv Apr 24, 2026
Temporal resolution of physiological monitoring in intensive care varies widely across healthcare systems. Artificial intelligence models assume a uniform and fixed frequency of sampling, thus limiting the generalizability of models, especially to re... read more 
health informatics

Semaglutide is associated with improved breast cancer survival, lower metastatic burden, and a dose-survival relationship uncoupled from weight-loss magnitude

medRxiv Apr 24, 2026
Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer, but whether incretin-based therapies confer survival benefit beyond weight loss remains unresolved. Using a federated electronic health record platf... read more 
oncology

Comparing Gleason Pattern 4 Measurement Approaches on Prostate Biopsy Using Machine Learning: A Proof-of-Principle Study

medRxiv Apr 24, 2026
Objective: To demonstrate the proof of principle that machine learning (ML) can be used to quantify Gleason Pattern (GP) 4 on digitized biopsy slides using multiple measurement approaches, allowing direct comparison of their prognostic performance. M... read more 
oncology
Popular Topics
Recent Journals