Artificial Intelligence Medical Compendium

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

Showing 52,371 to 52,380 of 225,279 articles

Interpretable Dynamic Network Modeling of Tensor Time Series via Kronecker Time-Varying Graphical Lasso

arXiv Feb 9, 2026
With the rapid development of web services, large amounts of time series data are generated and accumulated across various domains such as finance, healthcare, and online platforms. As such data often co-evolves with multiple variables interacting wi... read more 
Machine Learning stat.ML

Generative Regression for Left Ventricular Ejection Fraction Estimation from Echocardiography Video

arXiv Feb 9, 2026
Estimating Left Ventricular Ejection Fraction (LVEF) from echocardiograms constitutes an ill-posed inverse problem. Inherent noise, artifacts, and limited viewing angles introduce ambiguity, where a single video sequence may map not to a unique groun... read more 
Computer Vision and Pattern Recognition

Geospatial-Reasoning-Driven Vocabulary-Agnostic Remote Sensing Semantic Segmentation

arXiv Feb 9, 2026
Open-vocabulary semantic segmentation has emerged as a promising research direction in remote sensing, enabling the recognition of diverse land-cover types beyond pre-defined category sets. However, existing methods predominantly rely on the passive ... read more 
Computer Vision and Pattern Recognition

Chain-of-Caption: Training-free improvement of multimodal large language model on referring expression comprehension

arXiv Feb 9, 2026
Given a textual description, the task of referring expression comprehension (REC) involves the localisation of the referred object in an image. Multimodal large language models (MLLMs) have achieved high accuracy on REC benchmarks through scaling up ... read more 
Computer Vision and Pattern Recognition

Efficient-SAM2: Accelerating SAM2 with Object-Aware Visual Encoding and Memory Retrieval

arXiv Feb 9, 2026
Segment Anything Model 2 (SAM2) shows excellent performance in video object segmentation tasks; however, the heavy computational burden hinders its application in real-time video processing. Although there have been efforts to improve the efficiency ... read more 
Computer Vision and Pattern Recognition

Efficient-SAM2: Accelerating SAM2 with Object-Aware Visual Encoding and Memory Retrieval

arXiv Feb 9, 2026
Segment Anything Model 2 (SAM2) shows excellent performance in video object segmentation tasks; however, the heavy computational burden hinders its application in real-time video processing. Although there have been efforts to improve the efficiency ... read more 
Computer Vision and Pattern Recognition

A Unified Framework for Multimodal Image Reconstruction and Synthesis using Denoising Diffusion Models

arXiv Feb 9, 2026
Image reconstruction and image synthesis are important for handling incomplete multimodal imaging data, but existing methods require various task-specific models, complicating training and deployment workflows. We introduce Any2all, a unified framewo... read more 
Image and Video Processing cs.CV

Moving Beyond Functional Connectivity: Time-Series Modeling for fMRI-Based Brain Disorder Classification

arXiv Feb 9, 2026
Functional magnetic resonance imaging (fMRI) enables non-invasive brain disorder classification by capturing blood-oxygen-level-dependent (BOLD) signals. However, most existing methods rely on functional connectivity (FC) via Pearson correlation, whi... read more 
Computer Vision and Pattern Recognition

Inverting Data Transformations via Diffusion Sampling

arXiv Feb 9, 2026
We study the problem of transformation inversion on general Lie groups: a datum is transformed by an unknown group element, and the goal is to recover an inverse transformation that maps it back to the original data distribution. Such unknown transfo... read more 
Machine Learning cs.AI

CAE-AV: Improving Audio-Visual Learning via Cross-modal Interactive Enrichment

arXiv Feb 9, 2026
Audio-visual learning suffers from modality misalignment caused by off-screen sources and background clutter, and current methods usually amplify irrelevant regions or moments, leading to unstable training and degraded representation quality. To addr... read more 
Computer Vision and Pattern Recognition
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