Artificial Intelligence Medical Compendium

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

Showing 11,021 to 11,030 of 209,601 articles

Sleep-stage efficient classification using a lightweight self-supervised model

arXiv May 25, 2026
Accurate classification of sleep stages is crucial for diagnosing sleep disorders and automating this process can significantly enhance clinical assessments. This study aims to explore the use of a self-supervised model (more specifically, an adapted... read more 
Computer Vision and Pattern Recognition

CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection

arXiv May 25, 2026
Skin cancer is a common and fast rising malignancy worldwide. Early detection is critical for improving outcomes. Deep learning models trained on dermoscopic and clinical images can support automated and fast triage. However, many studies evaluate on... read more 
Computer Vision and Pattern Recognition

Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning

arXiv May 25, 2026
Parameter-efficient adaptation of vision-language foundation models is crucial for precise multimodal understanding of biomedical images, yet existing methods remain deterministic and often struggle under domain shift or ambiguous image-text alignmen... read more 
Computer Vision and Pattern Recognition cs.CL

A multifractal-based masked auto-encoder: an application to medical images

arXiv May 25, 2026
Masked autoencoders (MAE) have shown great promise in medical image classification. However, the random masking strategy employed by traditional MAEs may overlook critical areas in medical images, where even subtle changes can indicate disease. To ad... read more 
Computer Vision and Pattern Recognition

Benchmarking Convolutional, Transformer, Hybrid, and Vision Language Models for Multi Disease Retinal Screening

arXiv May 25, 2026
Modern deep learning offers powerful tools for automated retinal screening, but it remains unclear how different visual model families compare in realistic multi-disease settings and under domain shift. In this work, we benchmark twelve architectures... read more 
Computer Vision and Pattern Recognition cs.LG

VesselSim: learning 3D blood vessel segmentation without expert annotations

arXiv May 25, 2026
Blood vessel segmentation is a core task in medical image analysis for the care of vascular diseases and surgical planning, yet the challenges of providing expert vascular annotations pose a major obstacle for the progress of related deep learning te... read more 
Computer Vision and Pattern Recognition cs.AI

Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation

arXiv May 25, 2026
Semantic segmentation in complex environments such as urban driving scenes remains challenging under adverse lighting conditions, where RGB images alone provide insufficient information. RGB-Thermal fusion leverages the complementary strengths of vis... read more 
Computer Vision and Pattern Recognition

Prospective evaluation of multimodal respiratory failure prediction: Do chest X-rays improve performance beyond EHR signals?

arXiv May 25, 2026
Early prediction of respiratory failure is critical for timely clinical intervention in intensive care units. Existing electronic health record (EHR)-based models can continuously monitor physiologic deterioration, but they may not fully capture pulm... read more 
Image and Video Processing cs.AI cs.LG

LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV

arXiv May 25, 2026
Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing benchmarks primarily focus on 5--10 second text-conditioned generation ... read more 
Computer Vision and Pattern Recognition cs.MM cs.SD

RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation

arXiv May 25, 2026
Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable models. 3D Human motion, however, has lagged behind, constrained by an unsatisfying choice between... read more 
Computer Vision and Pattern Recognition
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