Artificial Intelligence Medical Compendium

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

Showing 40,111 to 40,120 of 223,737 articles

3D Gaussian Splatting with Self-Constrained Priors for High Fidelity Surface Reconstruction

arXiv Mar 20, 2026
Rendering 3D surfaces has been revolutionized within the modeling of radiance fields through either 3DGS or NeRF. Although 3DGS has shown advantages over NeRF in terms of rendering quality or speed, there is still room for improvement in recovering h... read more 
Computer Vision and Pattern Recognition

Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis

arXiv Mar 20, 2026
Rare cardiac anomalies are difficult to detect from electrocardiograms (ECGs) due to their long-tailed distribution with extremely limited case counts and demographic disparities in diagnostic performance. These limitations contribute to delayed reco... read more 
Computer Vision and Pattern Recognition

WorldAgents: Can Foundation Image Models be Agents for 3D World Models?

arXiv Mar 20, 2026
Given the remarkable ability of 2D foundation image models to generate high-fidelity outputs, we investigate a fundamental question: do 2D foundation image models inherently possess 3D world model capabilities? To answer this, we systematically evalu... read more 
Computer Vision and Pattern Recognition

PerformRecast: Expression and Head Pose Disentanglement for Portrait Video Editing

arXiv Mar 20, 2026
This paper primarily investigates the task of expression-only portrait video performance editing based on a driving video, which plays a crucial role in animation and film industries. Most existing research mainly focuses on portrait animation, which... read more 
Computer Vision and Pattern Recognition

ReLi3D: Relightable Multi-view 3D Reconstruction with Disentangled Illumination

arXiv Mar 20, 2026
Reconstructing 3D assets from images has long required separate pipelines for geometry reconstruction, material estimation, and illumination recovery, each with distinct limitations and computational overhead. We present ReLi3D, the first unified end... read more 
Computer Vision and Pattern Recognition cs.GR

Growing Networks with Autonomous Pruning

arXiv Mar 20, 2026
This paper introduces Growing Networks with Autonomous Pruning (GNAP) for image classification. Unlike traditional convolutional neural networks, GNAP change their size, as well as the number of parameters they are using, during training, in order to... read more 
Computer Vision and Pattern Recognition cs.LG

FREAK: A Fine-grained Hallucination Evaluation Benchmark for Advanced MLLMs

arXiv Mar 20, 2026
Multimodal Large Language Models (MLLMs) suffer from hallucinations. Existing hallucination evaluation benchmarks are often limited by over-simplified tasks leading to saturated metrics, or insufficient diversity that fails to adequately assess the h... read more 
Computer Vision and Pattern Recognition

Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression Generation from Histology Images

arXiv Mar 20, 2026
Spatial transcriptomics (ST) enables spot-level in situ expression profiling, but its high cost and limited throughput motivate predicting expression directly from HE-stained histology. Recent advances explore using score- or flow-based generative mo... read more 
Computer Vision and Pattern Recognition

Evaluating Image Editing with LLMs: A Comprehensive Benchmark and Intermediate-Layer Probing Approach

arXiv Mar 20, 2026
Evaluating text-guided image editing (TIE) methods remains a challenging problem, as reliable assessment should simultaneously consider perceptual quality, alignment with textual instructions, and preservation of original image content. Despite rapid... read more 
Computer Vision and Pattern Recognition

ReManNet: A Riemannian Manifold Network for Monocular 3D Lane Detection

arXiv Mar 20, 2026
Monocular 3D lane detection remains challenging due to depth ambiguity and weak geometric constraints. Mainstream methods rely on depth guidance, BEV projection, and anchor- or curve-based heads with simplified physical assumptions, remapping high-di... read more 
Computer Vision and Pattern Recognition
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