Artificial Intelligence Medical Compendium

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

Showing 14,641 to 14,650 of 212,071 articles

Case-Aware Medical Image Classification with Multimodal Knowledge Graphs and Reliability-Guided Refinement

arXiv May 21, 2026
Deep learning has brought significant progress to medical image classification, yet most existing methods still rely on isolated visual evidence and cannot effectively leverage similar cases or external knowledge. In clinical practice, diagnosis is t... read more 
Computer Vision and Pattern Recognition cs.AI

FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning

arXiv May 21, 2026
Fashion image retrieval is a cornerstone of modern e-commerce systems. A unified framework that supports diverse query formats and search intentions is highly desired in practice. However, existing approaches focus on narrow retrieval tasks and do no... read more 
Computer Vision and Pattern Recognition cs.MM

Cell Phantom Video Generation in Elliptical Fourier Descriptor Domain

arXiv May 21, 2026
Training Deep Neural Networks for tracking individual cells in biomedical videos requires a large amount of annotated data. The annotation of videos for cell tracking is very time consuming and often requires domain expertise; this explains the limit... read more 
Computer Vision and Pattern Recognition

VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis

arXiv May 21, 2026
Spatio-temporal reasoning is a core capability for Multimodal Large Language Models (MLLMs) operating in the real world. As such, evaluating it precisely has become an essential challenge. However, existing spatio-temporal reasoning benchmark dataset... read more 
Computer Vision and Pattern Recognition cs.AI

SegGuidedNet: Sub-Region-Aware Attention Supervision for Interpretable Brain Tumor Segmentation

arXiv May 21, 2026
Accurate segmentation of brain tumour sub-regions from multi-parametric MRI is critical for treatment planning yet remains challenging due to morphological variability, class imbalance, and overlapping appearances of tumour regions across imaging seq... read more 
Computer Vision and Pattern Recognition

SceneAligner: 3D-Grounded Floorplan Localization in the Wild

arXiv May 21, 2026
Many public buildings provide floorplans with a "you are here" indicator to help visitors orient themselves. Floorplan localization seeks to computationally replicate this capability by determining where visual observations were captured within a flo... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Rethinking Noise-Robust Training for Frozen Vision Foundation Models: A Cross-Dataset Benchmark with a Case Study of Small-Loss Failure

arXiv May 21, 2026
Frozen Vision Foundation Models (VFMs) with lightweight classification heads are increasingly used in medical imaging because they offer efficient and reproducible deployment. Yet noisy-label learning methods for this frozen-feature regime remain poo... read more 
Computer Vision and Pattern Recognition

Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection

arXiv May 21, 2026
Object detection from Unmanned Aerial Vehicles (UAVs) is challenged by severe ego-motion, camera jitter, and large scale variations. While modern detectors perform well on static images, their direct application to UAV video often fails, particularly... read more 
Robotics cs.CV

Benchmarking Machine Learning Architectures for Antimicrobial Stewardship in Pediatric ICUs

arXiv May 21, 2026
Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum antibiotic use, increasing antimicrobial resistance and potential long-term harms. Machine learning offers... read more 
Machine Learning

Healthcare LLM Benchmarks Are Only as Good as Their Explicit Assumptions

arXiv May 21, 2026
Benchmarks are necessary for healthcare evaluation, but are not sufficient for predicting deployment performance. Our position is that the evaluation--deployment gap arises not because of poorly designed benchmarks, but from implicit assumptions abou... read more 
Computers and Society cs.AI cs.LG
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