Artificial Intelligence Medical Compendium

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

Showing 1,401 to 1,410 of 163,745 articles

BEV-LLM: Leveraging Multimodal BEV Maps for Scene Captioning in Autonomous Driving

arXiv Jul 25, 2025
Autonomous driving technology has the potential to transform transportation, but its wide adoption depends on the development of interpretable and transparent decision-making systems. Scene captioning, which generates natural language descriptions ... read more 
Computer Vision and Pattern Recognition

A New One-Shot Federated Learning Framework for Medical Imaging Classification with Feature-Guided Rectified Flow and Knowledge Distillation

arXiv Jul 25, 2025
In multi-center scenarios, One-Shot Federated Learning (OSFL) has attracted increasing attention due to its low communication overhead, requiring only a single round of transmission. However, existing generative model-based OSFL methods suffer from... read more 
Computer Vision and Pattern Recognition Distributed, Parallel, and Cluster Computing

AEDR: Training-Free AI-Generated Image Attribution via Autoencoder Double-Reconstruction

arXiv Jul 25, 2025
The rapid advancement of image-generation technologies has made it possible for anyone to create photorealistic images using generative models, raising significant security concerns. To mitigate malicious use, tracing the origin of such images is e... read more 
Computer Vision and Pattern Recognition Cryptography and Security Image and Video Processing

MedSymmFlow: Bridging Generative Modeling and Classification in Medical Imaging through Symmetrical Flow Matching

arXiv Jul 25, 2025
Reliable medical image classification requires accurate predictions and well-calibrated uncertainty estimates, especially in high-stakes clinical settings. This work presents MedSymmFlow, a generative-discriminative hybrid model built on Symmetrica... read more 
Computer Vision and Pattern Recognition Artificial Intelligence

Neural Correction Operator: A Reliable and Fast Approach for Electrical Impedance Tomography

arXiv Jul 25, 2025
Electrical Impedance Tomography (EIT) is a non-invasive medical imaging method that reconstructs electrical conductivity mediums from boundary voltage-current measurements, but its severe ill-posedness renders direct operator learning with neural n... read more 
Numerical Analysis Numerical Analysis

Letter to the editor: multichannel deep learning prediction of major pathological response after neoadjuvant immunochemotherapy in lung cancer: a multicenter diagnostic study.

International journal of surgery (London, England) Jul 25, 2025
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Querying Autonomous Vehicle Point Clouds: Enhanced by 3D Object Counting with CounterNet

arXiv Jul 25, 2025
Autonomous vehicles generate massive volumes of point cloud data, yet only a subset is relevant for specific tasks such as collision detection, traffic analysis, or congestion monitoring. Effectively querying this data is essential to enable target... read more 
Computer Vision and Pattern Recognition Multimedia

Event-Driven Storytelling with Multiple Lifelike Humans in a 3D Scene

arXiv Jul 25, 2025
In this work, we propose a framework that creates a lively virtual dynamic scene with contextual motions of multiple humans. Generating multi-human contextual motion requires holistic reasoning over dynamic relationships among human-human and human... read more 
Computer Vision and Pattern Recognition

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD

arXiv Jul 25, 2025
Background: It is fundamental for accurate segmentation and quantification of the pulmonary vessel, particularly smaller vessels, from computed tomography (CT) images in chronic obstructive pulmonary disease (COPD) patients. Objective: The aim of t... read more 
Image and Video Processing Computer Vision and Pattern Recognition

Cross-Subject Mind Decoding from Inaccurate Representations

arXiv Jul 25, 2025
Decoding stimulus images from fMRI signals has advanced with pre-trained generative models. However, existing methods struggle with cross-subject mappings due to cognitive variability and subject-specific differences. This challenge arises from seq... read more 
Computer Vision and Pattern Recognition
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