Artificial Intelligence Medical Compendium

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

Showing 11,801 to 11,810 of 210,187 articles

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

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

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

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

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

Towards 3D heart mesh generation using contactless radar imaging and physics-informed neural network

arXiv May 25, 2026
Cardiac function evaluation necessitates continuous, non-invasive monitoring, a capability limited in MRI. Millimeter-wave (mmWave) radar and its Synthetic Aperture Radar (SAR) mode offer a privacy-preserving and portable point-of-care clinical appli... read more 
Computer Vision and Pattern Recognition

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models

arXiv May 25, 2026
We introduce AdvantageFlow, a forward-process reinforcement learning algorithm for rectified flow models. Unlike Flow-GRPO, which optimizes the reverse process, we optimize an advantage-weighted forward-process prediction loss. This optimization prob... read more 
Machine Learning cs.AI cs.CV

A Multimodal 3D Foundation Model for Light Sheet Fluorescence Microscopy Enables Few-Shot Segmentation, Classification, and Deblurring

arXiv May 25, 2026
Light sheet fluorescence microscopy (LSM) enables high-resolution, three-dimensional (3D) imaging of biological specimens, providing rich volumetric data for studying cellular organization, pathology, and vascular networks. However, the size, dimensi... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution

arXiv May 25, 2026
Creating images from noise is image generation; reconstructing fine details from coarse inputs is super-resolution. Despite their practical differences, both can be understood as reversing information loss across scales. We introduce $\textbf{SKILD}$... read more 
Computer Vision and Pattern Recognition cond-mat.stat-mech cs.AI cs.LG

DRScaffold: Boosting Dense-Scene Reasoning in Lightweight Vision Language Models

arXiv May 25, 2026
Lightweight vision-language models perform competitively on standard benchmarks yet fail systematically in dense-scene reasoning, where multiple objects, attributes, and relations must be jointly grounded and resolved through multi-step inference. Su... read more 
Computer Vision and Pattern Recognition cs.AI
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