Artificial Intelligence Medical Compendium

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

Showing 46,631 to 46,640 of 224,199 articles

Learning Disease-Sensitive Latent Interaction Graphs From Noisy Cardiac Flow Measurements

arXiv Feb 26, 2026
Cardiac blood flow patterns contain rich information about disease severity and clinical interventions, yet current imaging and computational methods fail to capture underlying relational structures of coherent flow features. We propose a physics-inf... read more 
Machine Learning

PackUV: Packed Gaussian UV Maps for 4D Volumetric Video

arXiv Feb 26, 2026
Volumetric videos offer immersive 4D experiences, but remain difficult to reconstruct, store, and stream at scale. Existing Gaussian Splatting based methods achieve high-quality reconstruction but break down on long sequences, temporal inconsistency,... read more 
Computer Vision and Pattern Recognition

RhythmBERT: A Self-Supervised Language Model Based on Latent Representations of ECG Waveforms for Heart Disease Detection

arXiv Feb 26, 2026
Electrocardiogram (ECG) analysis is crucial for diagnosing heart disease, but most self-supervised learning methods treat ECG as a generic time series, overlooking physiologic semantics and rhythm-level structure. Existing contrastive methods utilize... read more 
Machine Learning

Cytoarchitecture in Words: Weakly Supervised Vision-Language Modeling for Human Brain Microscopy

arXiv Feb 26, 2026
Foundation models increasingly offer potential to support interactive, agentic workflows that assist researchers during analysis and interpretation of image data. Such workflows often require coupling vision to language to provide a natural-language ... read more 
Computer Vision and Pattern Recognition

Locally Adaptive Decay Surfaces for High-Speed Face and Landmark Detection with Event Cameras

arXiv Feb 26, 2026
Event cameras record luminance changes with microsecond resolution, but converting their sparse, asynchronous output into dense tensors that neural networks can exploit remains a core challenge. Conventional histograms or globally-decayed time-surfac... read more 
Computer Vision and Pattern Recognition

SpectralMamba-UNet: Frequency-Disentangled State Space Modeling for Texture-Structure Consistent Medical Image Segmentation

arXiv Feb 26, 2026
Accurate medical image segmentation requires effective modeling of both global anatomical structures and fine-grained boundary details. Recent state space models (e.g., Vision Mamba) offer efficient long-range dependency modeling. However, their one-... read more 
Computer Vision and Pattern Recognition

WARM-CAT: : Warm-Started Test-Time Comprehensive Knowledge Accumulation for Compositional Zero-Shot Learning

arXiv Feb 26, 2026
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions based on the knowledge learned from seen ones. Existing methods suffer from performance degradation caused by the distribution shift of label space at test ... read more 
Computer Vision and Pattern Recognition

WARM-CAT: Warm-Started Test-Time Comprehensive Knowledge Accumulation for Compositional Zero-Shot Learning

arXiv Feb 26, 2026
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions based on the knowledge learned from seen ones. Existing methods suffer from performance degradation caused by the distribution shift of label space at test ... read more 
Computer Vision and Pattern Recognition

Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation

arXiv Feb 26, 2026
Adversarial transferability refers to the capacity of adversarial examples generated on the surrogate model to deceive alternate, unexposed victim models. This property eliminates the need for direct access to the victim model during an attack, there... read more 
Computer Vision and Pattern Recognition cs.AI

TriLite: Efficient Weakly Supervised Object Localization with Universal Visual Features and Tri-Region Disentanglement

arXiv Feb 26, 2026
Weakly supervised object localization (WSOL) aims to localize target objects in images using only image-level labels. Despite recent progress, many approaches still rely on multi-stage pipelines or full fine-tuning of large backbones, which increases... read more 
Computer Vision and Pattern Recognition
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