Artificial Intelligence Medical Compendium

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

Showing 2,081 to 2,090 of 213,633 articles

Prospective clinical indication, post-hoc report leakage, and fusion design in multi-image chest radiograph classification: a patient-clustered evaluation

arXiv Jul 15, 2026
Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at different stages of care. We evaluated 15,000 ReXGradient-160K studies with two readable images and five... read more 
Image and Video Processing cs.CV

AspectCLIP: Optimizing CLIP Representation Space via Aspect-Guided Consistency Regularization

arXiv Jul 15, 2026
Contrastive Language-Image Pretraining learns a shared representation space through large-scale contrastive learning. However, existing methods that enforce global consistency regularization overlook a key challenge: the inherent information asymmetr... read more 
Computer Vision and Pattern Recognition

AspectCLIP: Optimizing CLIP Representation Space via Aspect-Guided Consistency Regularization

arXiv Jul 15, 2026
Contrastive Language-Image Pretraining learns a shared representation space through large-scale contrastive learning. However, existing methods that enforce global consistency regularization overlook a key challenge: the inherent information asymmetr... read more 
Computer Vision and Pattern Recognition

TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model

arXiv Jul 15, 2026
We introduce TCAM-Diff, a novel 3D medical image generation model that reduces the memory requirements to encode and generate high-resolution 3D data. This model utilizes a decoder-only autoencoder method to learn triplane representation from dense v... read more 
Image and Video Processing cs.CV

Multimodal Assessment of Pancreatic Cancer Resectability Using Deep Learning

arXiv Jul 15, 2026
Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic vessels on CT imaging, yet expert assessment often shows substantial variability. We introduce a fu... read more 
Computer Vision and Pattern Recognition cs.AI cs.IR cs.LG

Heavy-Tailed Flow Matching via Random Clocks

arXiv Jul 15, 2026
Heavy-tailed data arise in many domains where rare events carry disproportionate importance, such as imbalanced image datasets, financial returns, and weather extremes. Standard diffusion and flow-matching models typically begin from Gaussian noise o... read more 
Machine Learning stat.ML

Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models

arXiv Jul 15, 2026
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric imaging remains hindered by prohibitive annotation costs and dataset opacity. Current data formats... read more 
Computer Vision and Pattern Recognition

AI-Augmented Adaptive Digital Twin Modeling for Brain Tumor Evolution Prediction and Treatment Scheduling

arXiv Jul 15, 2026
Brain tumor progression exhibits spatially heterogeneous growth, patient-specific treatment response, and complex interactions with surrounding anatomy, making accurate long-term prediction challenging. We propose an AI-augmented adaptive digital twi... read more 
Machine Learning

Fine-Grained Vision-Language Pretraining with Organ-Conditioned Pattern Tokens for CT Understanding

arXiv Jul 15, 2026
Computed tomography (CT) vision-language pretraining from paired volumes and radiology reports is a scalable yet challenging task. Existing methods commonly adopt global scan-report contrast, which is scalable but obscures heterogeneous organ evidenc... read more 
Computer Vision and Pattern Recognition

An Efficient Newton Algorithm for Nonnegative Matrix Factorization with the Kullback-Leibler Divergence

arXiv Jul 15, 2026
Nonnegative Matrix Factorization (NMF) is a fundamental tool in unsupervised learning, which approximates a nonnegative matrix by the product of two low-rank nonnegative factors. The Kullback-Leibler (KL) divergence is best suited to measure the data... read more 
Machine Learning
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