Artificial Intelligence Medical Compendium

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

Showing 36,301 to 36,310 of 223,137 articles

Towards Clinical Integration of Deep Learning-Based Classification of Urinary Sediment Particles from Digital Microscopy Images: A Prospective Study.

Clinical chemistry Apr 2, 2026
BACKGROUND: Urinalysis is a standard clinical test that includes the microscopic examination of urinary sediment to identify formed elements. Manual evaluation by laboratory technicians is time-intensive and subject to human error. Automated analysis... read more 

Multicenter Histology Image Integration and Multiscale Deep Learning Support Machine Learning-Enabled Pediatric Sarcoma Classification.

Cancer research Apr 2, 2026
UNLABELLED: Pediatric sarcomas present diagnostic challenges due to their rarity and diverse subtypes, often requiring specialized pathology expertise and costly genetic tests. To overcome these barriers, we developed a computational pipeline leverag... read more 

Artificial Intelligence, Connected Care, and Enabling Digital Health Technologies in Rare Diseases With a Focus on Lysosomal Storage Disorders: Scoping Review.

Journal of medical Internet research Apr 2, 2026
BACKGROUND: Rare diseases affect more than 300 million people globally, and only about 5% have approved therapies. Lysosomal storage disorders (LSDs) exemplify the diagnostic and long-term care complexity typical of rare diseases, and digital health ... read more 

AI foundation models for RNA biology.

RNA biology Apr 2, 2026
RNA biology is undergoing a transformative revolution driven by AI foundation models. These models learn the intricate relationships between RNA sequence, structure, and function by training on vast, diverse datasets spanning millions of RNA molecule... read more 

Label Shift Estimation With Incremental Prior Update

arXiv Apr 2, 2026
An assumption often made in supervised learning is that the training and testing sets have the same label distribution. However, in real-life scenarios, this assumption rarely holds. For example, medical diagnosis result distributions change over tim... read more 
Machine Learning

Moiré Video Authentication: A Physical Signature Against AI Video Generation

arXiv Apr 2, 2026
Recent advances in video generation have made AI-synthesized content increasingly difficult to distinguish from real footage. We propose a physics-based authentication signature that real cameras produce naturally, but that generative models cannot f... read more 
Computer Vision and Pattern Recognition cs.AI cs.MM

Can Video Diffusion Models Predict Past Frames? Bidirectional Cycle Consistency for Reversible Interpolation

arXiv Apr 2, 2026
Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have improved visual fidelity, they predominantly operate in a unidirection... read more 
Computer Vision and Pattern Recognition cs.MM

End-to-End Shared Attention Estimation via Group Detection with Feedback Refinement

arXiv Apr 2, 2026
This paper proposes an end-to-end shared attention estimation method via group detection. Most previous methods estimate shared attention (SA) without detecting the actual group of people focusing on it, or assume that there is a single SA point in a... read more 
Computer Vision and Pattern Recognition

SteerFlow: Steering Rectified Flows for Faithful Inversion-Based Image Editing

arXiv Apr 2, 2026
Recent advances in flow-based generative models have enabled training-free, text-guided image editing by inverting an image into its latent noise and regenerating it under a new target conditional guidance. However, existing methods struggle to prese... read more 
Computer Vision and Pattern Recognition

LiteInception: A Lightweight and Interpretable Deep Learning Framework for General Aviation Fault Diagnosis

arXiv Apr 2, 2026
General aviation fault diagnosis and efficient maintenance are critical to flight safety; however, deploying deep learning models on resource-constrained edge devices poses dual challenges in computational capacity and interpretability. This paper pr... read more 
Artificial Intelligence cs.LG
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