Artificial Intelligence Medical Compendium

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

Showing 10,091 to 10,100 of 208,614 articles

Deployment-complete benchmarking

arXiv May 25, 2026
Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports only the response it records, not necessarily the deployment action. We introduce deployment-complete benchmarking, which tests whether benchmark evi... read more 
Machine Learning stat.ML

LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence

arXiv May 25, 2026
We introduce LLaVA-OneVision-2 (LLaVA-OV-2), the most capable vision-language model in the LLaVA-OneVision series to date, achieving superior performance across a broad range of multimodal benchmarks. The model builds on a native OneVision-Encoder an... read more 
Computer Vision and Pattern Recognition

PathWISE: Multi-Agent Cancer Pathway Triaging Ontology Learning from Clinical Flowcharts

arXiv May 25, 2026
Clinical pathways are disseminated as visual flowcharts where spatial topology, arrow direction, colour coding, and font weight encode critical triage logic that remains inaccessible to computational systems. We present PathWISE, a five-phase pipelin... read more 
Computer Vision and Pattern Recognition

Context-driven Missing-Modality Learning for Robust Medical Diagnosis with Image-Tabular Data

arXiv May 25, 2026
While multimodal data integrating diverse imaging and clinical tabular records is crucial for accurate medical diagnosis, the arbitrary absence of specific modalities is prevalent in clinical practice, severely degrading the performance of multimodal... read more 
Computer Vision and Pattern Recognition

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing

arXiv May 25, 2026
Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual review and transcription. The original RAPTOR system used Large Language Models for structured extractio... read more 
Computer Vision and Pattern Recognition

EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory

arXiv May 25, 2026
Ultrasound video segmentation is clinically valuable yet difficult due to speckle noise, weak boundaries, and rapid anatomical deformation. Recent promptable foundation models enable point-guided segmentation, but their direct deployment in ultrasoun... read more 
Computer Vision and Pattern Recognition cs.AI

LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data

arXiv May 25, 2026
Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to commercial photography and package delivery. With the increasing prevalence of UAVs, it becomes criti... read more 
Computer Vision and Pattern Recognition cs.RO

How Accurate are Video Quality Models for Diffusion-Based Video Super-Resolution?

arXiv May 25, 2026
Recent video super-resolution (VSR) approaches use deep neural networks to enhance low-quality input videos and recover visual detail, with diffusion-based methods in particular showing promising results. In this paper, we investigate whether existin... read more 
Image and Video Processing cs.CV

Quantitative Evaluation of the Severity of Posttraumatic Stress Disorder through Transfer Learning from Specific Phobia Data

arXiv May 25, 2026
Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current clinical assessments of PTSD often rely on subjective evaluations, which can be time-consuming, costl... read more 
Machine Learning cs.AI

AgentGrounder: Zero-Shot 3D Visual Pointcloud Grounding using Multimodal Language Models

arXiv May 25, 2026
3D Visual Grounding (3DVG) is an essential capability for embodied AI, requiring agents to localize objects in 3D scenes based on natural language descriptions. Recent zero-shot methods leverage 2D vision-language models (LVLMs). However, they often ... read more 
Computer Vision and Pattern Recognition cs.RO
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