Artificial Intelligence Medical Compendium

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

Showing 28,121 to 28,130 of 219,064 articles

Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces

arXiv Apr 22, 2026
Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often incomplete, with discontinuous traces and sometimes entirely missing layers, due to limited resolu... read more 
Machine Learning

LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

arXiv Apr 22, 2026
We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a natively integrated framework. Its architecture combines a fully semantic discrete tokenizer, a MoE-based... read more 
Computer Vision and Pattern Recognition

LEXIS: LatEnt ProXimal Interaction Signatures for 3D HOI from an Image

arXiv Apr 22, 2026
Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing the subtle physical coupling between the body and objects. While current methods rely on sparse, ... read more 
Computer Vision and Pattern Recognition cs.LG

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model

arXiv Apr 22, 2026
Large vision-language models (LVLMs) have made substantial advances in reasoning tasks at the Olympiad level. Nevertheless, current Olympiad-level multimodal reasoning benchmarks for these models often emphasize single-image analysis and fail to expl... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL

Adapting TrOCR for Printed Tigrinya Text Recognition: Word-Aware Loss Weighting for Cross-Script Transfer Learning

arXiv Apr 22, 2026
Transformer-based OCR models have shown strong performance on Latin and CJK scripts, but their application to African syllabic writing systems remains limited. We present the first adaptation of TrOCR for printed Tigrinya using the Ge'ez script. Star... read more 
Computer Vision and Pattern Recognition

ParetoSlider: Diffusion Models Post-Training for Continuous Reward Control

arXiv Apr 22, 2026
Reinforcement Learning (RL) post-training has become the standard for aligning generative models with human preferences, yet most methods rely on a single scalar reward. When multiple criteria matter, the prevailing practice of ``early scalarization'... read more 
Machine Learning cs.CV

Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples

arXiv Apr 22, 2026
The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch effects critically undermine experimental reproducibility and are the primary cause of failure of... read more 
Machine Learning q-bio.QM

An Interpretable Machine-Learning Model for Predicting Occult Central Lymph Node Metastasis in Papillary Thyroid Cancer.

The Journal of clinical endocrinology and metabolism Apr 22, 2026
CONTEXT: Accurate preoperative prediction of occult lymph node metastasis (OLNM) in clinically lymph node negative (cN0) papillary thyroid carcinoma (PTC) is critical for optimizing therapeutic strategy, particularly for thermal ablation and active s... read more 

Graves' disease: a new era of pathophysiology-guided therapeutics.

The Journal of clinical endocrinology and metabolism Apr 22, 2026
Graves' disease (GD) is an autoimmune entity that had an unchanged treatment paradigm for more than half a century with radioactive iodine, antithyroid drugs (ATDs), and surgery representing the mainstay of therapy, with variation in their use over t... read more 

Attitudes, Needs, and Expectations Regarding the Application of AI in Occupational Healthcare: A Multiple Stakeholder Perspective.

Journal of occupational and environmental medicine Apr 21, 2026
OBJECTIVE: The aim of the study was to explore attitudes, needs, and expectations of employees, employers, and occupational health professionals regarding the application of AI in occupational healthcare. METHODS: Twenty-three semistructured intervie... read more 
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