Artificial Intelligence Medical Compendium

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

Showing 39,471 to 39,480 of 223,737 articles

CataractSAM-2: A Domain-Adapted Model for Anterior Segment Surgery Segmentation and Scalable Ground-Truth Annotation

arXiv Mar 23, 2026
We present CataractSAM-2, a domain-adapted extension of Meta's Segment Anything Model 2, designed for real-time semantic segmentation of cataract ophthalmic surgery videos with high accuracy. Positioned at the intersection of computer vision and medi... read more 
Computer Vision and Pattern Recognition cs.AI cs.DB cs.LG cs.RO

Rethinking Visual Privacy: A Compositional Privacy Risk Framework for Severity Assessment with VLMs

arXiv Mar 23, 2026
Existing visual privacy benchmarks largely treat privacy as a binary property, labeling images as private or non-private based on visible sensitive content. We argue that privacy is fundamentally compositional. Attributes that are benign in isolation... read more 
Computer Vision and Pattern Recognition

HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling

arXiv Mar 23, 2026
Regressing 3D rotations of objects from 2D images is a crucial yet challenging task, with broad applications in autonomous driving, virtual reality, and robotic control. Existing rotation regression models often rely on large amounts of labeled data ... read more 
Computer Vision and Pattern Recognition

A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

arXiv Mar 23, 2026
Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in multimodal foundation models have improved performance on various clinical tasks, most existing models r... read more 
Artificial Intelligence cs.CV

Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

arXiv Mar 23, 2026
Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in multimodal foundation models have improved performance on various clinical tasks, most existing models r... read more 
Artificial Intelligence cs.CV

AdaEdit: Adaptive Temporal and Channel Modulation for Flow-Based Image Editing

arXiv Mar 23, 2026
Inversion-based image editing in flow matching models has emerged as a powerful paradigm for training-free, text-guided image manipulation. A central challenge in this paradigm is the injection dilemma: injecting source features during denoising pres... read more 
Computer Vision and Pattern Recognition

Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff

arXiv Mar 23, 2026
In recent years, numerous data-intensive broadcasting applications have emerged at the wireless edge, calling for a flexible tradeoff between distortion, transmission rate, and processing complexity. While deep learning-based joint source-channel cod... read more 
Information Theory cs.LG eess.SP

Efficient Zero-Shot AI-Generated Image Detection

arXiv Mar 23, 2026
The rapid progress of text-to-image models has made AI-generated images increasingly realistic, posing significant challenges for accurate detection of generated content. While training-based detectors often suffer from limited generalization to unse... read more 
Computer Vision and Pattern Recognition cs.AI

PGR-Net: Prior-Guided ROI Reasoning Network for Brain Tumor MRI Segmentation

arXiv Mar 23, 2026
Brain tumor MRI segmentation is essential for clinical diagnosis and treatment planning, enabling accurate lesion detection and radiotherapy target delineation. However, tumor lesions occupy only a small fraction of the volumetric space, resulting in... read more 
Computer Vision and Pattern Recognition

TrustFed: Enabling Trustworthy Medical AI under Data Privacy Constraints

arXiv Mar 23, 2026
Protecting patient privacy remains a fundamental barrier to scaling machine learning across healthcare institutions, where centralizing sensitive data is often infeasible due to ethical, legal, and regulatory constraints. Federated learning offers a ... read more 
Machine Learning cs.CY
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