Artificial Intelligence Medical Compendium

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

Showing 30,221 to 30,230 of 220,100 articles

Personal Statements and the Human Evaluation of Artificial Intelligence.

Journal of the American College of Surgeons
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Optimizing automated sleep stage scoring of 5-s mini-epochs: a transfer learning study.

Sleep
STUDY OBJECTIVES: Conventional sleep staging relies on 30-s epochs, potentially concealing transient sleep stage intrusion and reducing precision. Building on our previous study of mini-epochs, we investigated whether U-Sleep, an existing automatic d... read more 

Towards Design Compositing

arXiv
Graphic design creation involves harmoniously assembling multimodal components such as images, text, logos, and other visual assets collected from diverse sources, into a visually-appealing and cohesive design. Recent methods have largely focused on ... read more 

Retrieve, Then Classify: Corpus-Grounded Automation of Clinical Value Set Authoring

arXiv
Clinical value set authoring -- the task of identifying all codes in a standardized vocabulary that define a clinical concept -- is a recurring bottleneck in clinical quality measurement and phenotyping. A natural approach is to prompt a large langua... read more 

High-Speed Full-Color HDR Imaging via Unwrapping Modulo-Encoded Spike Streams

arXiv
Conventional RGB-based high dynamic range (HDR) imaging faces a fundamental trade-off between motion artifacts in multi-exposure captures and irreversible information loss in single-shot techniques. Modulo sensors offer a promising alternative by enc... read more 

Physically-Induced Atmospheric Adversarial Perturbations: Enhancing Transferability and Robustness in Remote Sensing Image Classification

arXiv
Adversarial attacks pose a severe threat to the reliability of deep learning models in remote sensing (RS) image classification. Most existing methods rely on direct pixel-wise perturbations, failing to exploit the inherent atmospheric characteristic... read more 

Chaotic CNN for Limited Data Image Classification

arXiv
Convolutional neural networks (CNNs) often exhibit poor generalisation in limited training data scenarios due to overfitting and insufficient feature diversity. In this work, a simple and effective chaos-based feature transformation is proposed to en... read more 

Rethinking Patient Education as Multi-turn Multi-modal Interaction

arXiv
Most medical multimodal benchmarks focus on static tasks such as image question answering, report generation, and plain-language rewriting. Patient education is more demanding: systems must identify relevant evidence across images, show patients wher... read more 

DETR-ViP: Detection Transformer with Robust Discriminative Visual Prompts

arXiv
Visual prompted object detection enables interactive and flexible definition of target categories, thereby facilitating open-vocabulary detection. Since visual prompts are derived directly from image features, they often outperform text prompts in re... read more