Artificial Intelligence Medical Compendium

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

Showing 1,651 to 1,660 of 213,568 articles

CRAFT: Clustering Rubrics to Diagnose Weak LLM Capabilities and Generate Targeted Fine-Tuning Data

arXiv Jul 17, 2026
Evaluations should do more than measure a models current performance. They should tell us what to fix for the next model iteration and provide a way to generate targeted post training data. Most evaluation pipelines identify weak examples, topics, or... read more 
Artificial Intelligence cs.LG

Toward Semantic Communication for Real-time Mobile 3D Reconstruction

arXiv Jul 17, 2026
Real-time mobile 3D reconstruction is fundamental to many emerging applications such as autonomous navigation and digital twin construction, where a moving platform continuously captures an image stream and transmit to a computing server for scene un... read more 
Computer Vision and Pattern Recognition cs.MA cs.MM

Knowing the Self, Understanding the World: A Dual-Cognition Benchmark for UAV Spatio-temporal Reasoning with MLLMs

arXiv Jul 17, 2026
Multimodal large language models have achieved strong performance across diverse vision-language tasks, yet their capabilities in UAV scenarios remain insufficiently explored. Recent UAV-oriented benchmarks have begun to evaluate MLLMs in aerial scen... read more 
Computer Vision and Pattern Recognition

Learned ultrasound segmentation and deformable CT fusion for augmented reality endovascular surgery

medRxiv Jul 17, 2026
Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X-ray imaging, which provides limited depth perception and exposes patients and clinicians to ionizin... read more 
cardiovascular medicine

A ReAct Agentic AI System for Natural Language Querying and Statistical Analysis of The Cancer Genome Atlas Clinical Data

medRxiv Jul 17, 2026
The Cancer Genome Atlas (TCGA) holds clinical data for over 11,000 patients across 33 cancer types, but access is hard because of complex file structures, heterogeneous formats, and the need for programming. We present an agentic system for natural l... read more 
health informatics

Scaling ECG Foundation Models and Identifying a Threshold for Effective Representation Learning

medRxiv Jul 17, 2026
We conducted a scaling evaluation of unlabeled pretraining for electrocardiogram foundation model performance. One-dimensional vision transformer masked autoencoders were pretrained across increasing ECG volumes and fine-tuned for rhythm, morphology,... read more 
cardiovascular medicine

Statistical Inference and Power Analysis for Comparative F1 and Fβ Scores under Correlated Classifier Pairs

medRxiv Jul 17, 2026
As machine learning and artificial intelligence systems are increasingly used in healthcare, rigorous evaluation of their classification performance has become critical. The F1 and F{beta} scores are widely adopted metrics for assessing performance i... read more 
dermatology

Reconsidering the case against risk prediction in self-harm: routinely collected health data distinguishes groups at higher and lower risk of adverse outcomes following paracetamol overdose

medRxiv Jul 17, 2026
Background. UK clinical guidance recommends that structured risk prediction tools and risk stratification should not be used in self-harm, to predict suicide or determine who is offered treatment. Underpinning this position is the premise that routin... read more 
psychiatry and clinical psychology

Machine learning combining FIT with up to 1,025 clinical variables: limited referral reduction but potential for faster diagnosis

medRxiv Jul 17, 2026
Background The faecal immunochemical test (FIT) is central to triaging symptomatic patients with suspected colorectal cancer (CRC) in UK primary care, yet only about one in eleven patients above the NICE 10 ug/g threshold have CRC. Existing predictio... read more 
primary care research

Large Language Model - Enhanced Decision Tree Framework for Identifying Multiple Sclerosis Diagnoses from Clinical Documentation

medRxiv Jul 17, 2026
Background. Early diagnosis and intervention are crucial in multiple sclerosis (MS), yet diagnostic delays are common. Large language models (LLMs) such as generative pre-trained transformers (GPTs) may help streamline diagnostic workflows by extract... read more 
neurology
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