Artificial Intelligence Medical Compendium

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

Showing 11,871 to 11,880 of 210,187 articles

AI-Driven SERS for Non-invasive and Label-Free Extracellular Vesicle Detection Across Cellular Origins in Tears and Sweat

arXiv May 25, 2026
Wearable sensing technology capable of point-of-care, continuous and non-invasive analysis of exosomes in biofluid such as tears and sweat is an essential part for future personalized medicine. Major detection and identification methods of cell secre... read more 
Mesoscale and Nanoscale Physics physics.data-an physics.optics q-bio.QM

MAIL++: Multi-Modal Bi-directional Agent Layer for Vision-Language Models

arXiv May 25, 2026
Adapting large vision-language models (VLMs) such as CLIP to downstream tasks remains challenging, as full fine-tuning is computationally prohibitive and prone to overfitting in low-data regimes. Parameter-efficient fine-tuning (PEFT) alleviates thes... read more 
Computer Vision and Pattern Recognition

Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation

arXiv May 25, 2026
Audio-driven talking-head generation has achieved remarkable progress with recent models such as AniTalker, FLOAT, and Sonic. Despite their success, most existing approaches rely on a single static reference image to condition the entire video genera... read more 
Computer Vision and Pattern Recognition cs.AI cs.MM

Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis

arXiv May 25, 2026
Breast ultrasound imaging is an important noninvasive method for early breast cancer diagnosis, but automatic benign/malignant classification remains challenging due to tumor heterogeneity, blurred boundaries, and data imbalance. To improve feature r... read more 
Computer Vision and Pattern Recognition cs.AI

Location Prior Generation via Multi-Source Urban Data Fusion for Low-Altitude Air Mobility

arXiv May 25, 2026
Building height, the third dimension (3D) of urban spatial data, is absent in over 95% of structures in global geospatial databases. For the emerging low-altitude economy, this data gap forces each aerial platform to rely on real-time onboard sensing... read more 
Computer Vision and Pattern Recognition

A Multimodal Framework for Dementia Detection via Linguistic and Acoustic Representation Learning

arXiv May 25, 2026
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, and daily functioning. Early diagnosis is particularly important, as timely intervention may help slow... read more 
Sound cs.LG

Are We Overconfident in Models and Results for Semi-Supervised 3D Medical Image Segmentation?

arXiv May 25, 2026
Semi-supervised learning has become a dominant paradigm for reducing annotation costs. However, we argue that the current progress is clouded by a twofold overconfidence problem. Algorithmically, mainstream pseudo-labeling frameworks often conflate p... read more 
Computer Vision and Pattern Recognition

Rethinking Scribble-Guided Image Editing: Generalization, Instruction Adherence, and Multi-Tasking

arXiv May 25, 2026
Scribble-guided image editing allows users to combine simple scribble annotations with text prompts to specify both where and how an image should be edited, enabling flexible interaction with precise spatial control. However, existing models still ex... read more 
Computer Vision and Pattern Recognition

ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

arXiv May 25, 2026
Existing deep learning-based low-light enhancement methods are typically trained on limited datasets with single enhancement targets, which restricts their generalization ability and controllability in real-world applications. To overcome these limit... read more 
Computer Vision and Pattern Recognition

ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

arXiv May 25, 2026
Existing deep learning-based low-light enhancement methods are typically trained on limited datasets with single enhancement targets, which restricts their generalization ability and controllability in real-world applications. To overcome these limit... read more 
Computer Vision and Pattern Recognition
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