Artificial Intelligence Medical Compendium

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

Showing 22,831 to 22,840 of 216,842 articles

OphMAE: Bridging Volumetric and Planar Imaging with a Foundation Model for Adaptive Ophthalmological Diagnosis

arXiv May 4, 2026
The advent of foundation models has heralded a new era in medical artificial intelligence (AI), enabling the extraction of generalizable representations from large-scale unlabeled datasets. However, current ophthalmic AI paradigms are predominantly c... read more 
Computer Vision and Pattern Recognition cs.AI

PubMed-Ophtha: An open resource for training ophthalmology vision-language models on scientific literature

arXiv May 4, 2026
Vision-language models hold considerable promise for ophthalmology, but their development depends on large-scale, high-quality image-text datasets that remain scarce. We present PubMed-Ophtha, a hierarchical dataset of 102,023 ophthalmological image-... read more 
Computer Vision and Pattern Recognition cs.CL

Visual Latents Know More Than They Say: Unsilencing Latent Reasoning in MLLMs

arXiv May 4, 2026
Continuous latent-space reasoning offers a compact alternative to textual chain-of-thought for multimodal models, enabling high-dimensional visual evidence to be integrated without explicit reasoning tokens. However, we identify a previously overlook... read more 
Machine Learning

SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Training

arXiv May 4, 2026
Synthetic training has recently advanced brain MRI segmentation by enabling contrast-agnostic models trained entirely on generated data. However, most existing approaches rely on hundreds of automatically labeled templates, introducing systematic bia... read more 
Computer Vision and Pattern Recognition

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

arXiv May 4, 2026
Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-small cell lung cancer (NSCLC). While [$^{18}$F]FDG PET/CT is a standard tool for the clinical evaluati... read more 
Computer Vision and Pattern Recognition cs.AI

Does it Really Count? Assessing Semantic Grounding in Text-Guided Class-Agnostic Counting

arXiv May 4, 2026
Open-world text-guided class-agnostic counting (CAC) has emerged as a flexible paradigm for counting arbitrary object classes by using natural language prompts. However, current evaluation protocols primarily focus on standard counting errors within ... read more 
Computer Vision and Pattern Recognition

TOC-SR: Task-Optimal Compact diffusion for Image Super Resolution

arXiv May 4, 2026
Diffusion models have recently demonstrated strong performance for image restoration tasks, including super-resolution. However, their large model size and iterative sampling procedures make them computationally expensive for practical deployment. In... read more 
Computer Vision and Pattern Recognition cs.AI

Linearizing Vision Transformer with Test-Time Training

arXiv May 4, 2026
While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for overcoming the quadratic bottleneck, training such models from scratch remains prohibitively expensive. Inheriting weights from pretrained Transformer... read more 
Computer Vision and Pattern Recognition

HumanSplatHMR: Closing the Loop Between Human Mesh Recovery and Gaussian Splatting Avatar

arXiv May 4, 2026
Accurately recovering human pose and appearance from video is an essential component of scene reconstruction, with applications to motion capture, motion prediction, virtual reality, and digital twinning. Despite significant interest in building real... read more 
Computer Vision and Pattern Recognition

Compositional Neural-Cyber-Physical System Verification in the Interactive Theorem Prover of Your Choice

arXiv May 4, 2026
Formal verification of neuro-symbolic cyber-physical systems, such as drones, medical devices and robots, is complicated. Neural components must be trained to be optimal with respect to the available data as well as the safety specifications, and the... read more 
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