Artificial Intelligence Medical Compendium

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

Showing 32,821 to 32,830 of 221,227 articles

RIRF: Reasoning Image Restoration Framework

arXiv Apr 10, 2026
Universal image restoration (UIR) aims to recover clean images from diverse and unknown degradations using a unified model. Existing UIR methods primarily focus on pixel reconstruction and often lack explicit diagnostic reasoning over degradation com... read more 
Computer Vision and Pattern Recognition

Envisioning the Future, One Step at a Time

arXiv Apr 10, 2026
Accurately anticipating how complex, diverse scenes will evolve requires models that represent uncertainty, simulate along extended interaction chains, and efficiently explore many plausible futures. Yet most existing approaches rely on dense video o... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning

arXiv Apr 10, 2026
Large Vision Language Models (LVLMs) achieve strong multimodal reasoning but frequently exhibit hallucinations and incorrect responses with high certainty, which hinders their usage in high-stakes domains. Existing verbalized confidence calibration m... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL

VisionFoundry: Teaching VLMs Visual Perception with Synthetic Images

arXiv Apr 10, 2026
Vision-language models (VLMs) still struggle with visual perception tasks such as spatial understanding and viewpoint recognition. One plausible contributing factor is that natural image datasets provide limited supervision for low-level visual skill... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL

Seeing is Believing: Robust Vision-Guided Cross-Modal Prompt Learning under Label Noise

arXiv Apr 10, 2026
Prompt learning is a parameter-efficient approach for vision-language models, yet its robustness under label noise is less investigated. Visual content contains richer and more reliable semantic information, which remains more robust under label nois... read more 
Computer Vision and Pattern Recognition cs.AI

Case-Grounded Evidence Verification: A Framework for Constructing Evidence-Sensitive Supervision

arXiv Apr 10, 2026
Evidence-grounded reasoning requires more than attaching retrieved text to a prediction: a model should make decisions that depend on whether the provided evidence supports the target claim. In practice, this often fails because supervision is weak, ... read more 
Computation and Language cs.AI cs.IR cs.LG

MRDGNN: A multi-relational reasoning framework for predicting drug indications via relational digraphs.

Computational biology and chemistry Apr 10, 2026
Predicting drug indications is a fundamental task in biomedical research and drug repurposing. In addition to known therapeutic associations, clinically relevant but opposite signals, such as contraindications, may provide complementary evidence for ... read more 

Restoring auditory discrimination in noise: mismatch negativity evidence for a deep neural network-based denoising system in hearing aids.

Hearing research Apr 10, 2026
BACKGROUND: Understanding speech in noise is a primary challenge for individuals with sensorineural hearing loss (SNHL). While deep neural network (DNN)-based noise reduction in hearing aids shows behavioral promise, objective neurophysiological evid... read more 

Tear fluid multi-omics and biosensor integration for diagnosis and personalized therapeutics in dry eye disease.

Experimental eye research Apr 10, 2026
Dry Eye Disease (DED) is increasingly recognized as a complicated, multi-factorial disease involving oxidative damage, metabolic dysregulation and immune dysregulation on the ocular surface. New data emerging from proteomics, lipidomics, metabolomics... read more 

An Introduction to Machine Learning for the Pediatric Hospitalist.

Hospital pediatrics Apr 10, 2026
Machine learning models are increasingly used in clinical research to predict patient outcomes, yet many clinicians lack the training to critically appraise these studies. This article provides a conceptual introduction to machine learning for the pe... read more 
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