Artificial Intelligence Medical Compendium

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

Showing 14,631 to 14,640 of 212,071 articles

Towards Clinically Interpretable Ophthalmic VQA via Spatially-Grounded Lesion Evidence

arXiv May 21, 2026
Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmology, where retinal fundus photography is essential for diagnosis. However, ophthalmic VQA benchmarks primarily emphasize answer accuracy, neglecting t... read more 
Computer Vision and Pattern Recognition cs.AI

Moment-Reenacting: Inverse Motion Degradation with Cross-shutter Guidance

arXiv May 21, 2026
Motion degradation, manifested as blur in global shutter (GS) images or rolling shutter (RS) distortion in RS counterparts, remains a fundamental challenge in computational imaging, especially under fast motion or low-light conditions. While prior wo... read more 
Computer Vision and Pattern Recognition

Making the Discrete Continuous: Synthetic RAW Augmentations for Fine-Grained Evaluation of Person Detection Performance in Low Light

arXiv May 21, 2026
Real-world deployment of AI vision models is both fueled and limited by the data available for training and testing. Real datasets are sparse and uneven: long-tailed or unbalanced distributions hinder generalization, and the low number of samples in ... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG physics.optics

SADGE: Structure and Appearance Domain Gap Estimation of Synthetic and Real Data

arXiv May 21, 2026
We propose SADGE, a quantitative similarity metric that predicts the performance of synthetic image datasets for common computer vision tasks without downstream model training. Estimating whether a synthetic dataset will lead to a model that performs... read more 
Computer Vision and Pattern Recognition

BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series

arXiv May 21, 2026
Cross-subject generalization in biomedical time-series refers to training on data from some subjects and testing on unseen subjects.The key challenge is to suppress subject specific variability in BTS representations.Most existing methods implicitly ... read more 
Machine Learning cs.AI

MaSC: A Masked Similarity Metric for Evaluating Concept-Driven Generation

arXiv May 21, 2026
Evaluating single-concept personalization in text-to-image diffusion requires measuring both concept preservation, which captures identity fidelity to a reference, and prompt following, which captures whether the generated scene matches the prompt. E... read more 
Computer Vision and Pattern Recognition

Matching with Deliberation: Test-Time Evolutionary Hierarchical Multi-Agents for Zero-Shot Compositional Image Retrieval

arXiv May 21, 2026
Zero-Shot Compositional Image Retrieval (ZS-CIR) requires both preserving the visual continuity of the reference image and faithfully executing the semantic variables specified in the modification text, which constitutes the core challenge of the tas... read more 
Computer Vision and Pattern Recognition

Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling

arXiv May 21, 2026
Vision-Language Models (VLMs) excel at tasks like zero-shot classification and cross-modal retrieval by mapping images and text to a shared space, but this requires expensive end-to-end training with massive paired datasets. Current post-hoc alignmen... read more 
Computer Vision and Pattern Recognition

Training-Free Fine-Grained Semantic Segmentations in Low Data Regimes: A FungiTastic Baseline

arXiv May 21, 2026
Fine-grained semantic segmentation requires both precise localization and discrimination between visually similar classes. In FungiTastic, this problem is further complicated by a long-tailed distribution and strong variation in image acquisition con... read more 
Computer Vision and Pattern Recognition

SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation

arXiv May 21, 2026
Multimodal Large Language Models (MLLMs) have made rapid progress in spatial intelligence, yet existing spatial reasoning benchmarks largely assume pristine visual inputs and overlook the degradations that commonly occur in real-world deployment, suc... read more 
Computer Vision and Pattern Recognition cs.CL
Popular Topics
Recent Journals