Artificial Intelligence Medical Compendium

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

Showing 55,461 to 55,470 of 226,647 articles

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

arXiv Feb 2, 2026
Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, evaluating these visual and textual search abilities is still difficult, ... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL cs.LG

SurvKAN: A Fully Parametric Survival Model Based on Kolmogorov-Arnold Networks

arXiv Feb 2, 2026
Accurate prediction of time-to-event outcomes is critical for clinical decision-making, treatment planning, and resource allocation in modern healthcare. While classical survival models such as Cox remain widely adopted in standard practice, they rel... read more 
Machine Learning cs.AI

CIEC: Coupling Implicit and Explicit Cues for Multimodal Weakly Supervised Manipulation Localization

arXiv Feb 2, 2026
To mitigate the threat of misinformation, multimodal manipulation localization has garnered growing attention. Consider that current methods rely on costly and time-consuming fine-grained annotations, such as patch/token-level annotations. This paper... read more 
Computer Vision and Pattern Recognition

Lung Nodule Image Synthesis Driven by Two-Stage Generative Adversarial Networks

arXiv Feb 2, 2026
The limited sample size and insufficient diversity of lung nodule CT datasets severely restrict the performance and generalization ability of detection models. Existing methods generate images with insufficient diversity and controllability, sufferin... read more 
Computer Vision and Pattern Recognition

Eliminating Registration Bias in Synthetic CT Generation: A Physics-Based Simulation Framework

arXiv Feb 2, 2026
Supervised synthetic CT generation from CBCT requires registered training pairs, yet perfect registration between separately acquired scans remains unattainable. This registration bias propagates into trained models and corrupts standard evaluation m... read more 
Computer Vision and Pattern Recognition

Toxicity Assessment in Preclinical Histopathology via Class-Aware Mahalanobis Distance for Known and Novel Anomalies

arXiv Feb 2, 2026
Drug-induced toxicity remains a leading cause of failure in preclinical development and early clinical trials. Detecting adverse effects at an early stage is critical to reduce attrition and accelerate the development of safe medicines. Histopatholog... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Enhancing Diffusion-Based Quantitatively Controllable Image Generation via Matrix-Form EDM and Adaptive Vicinal Training

arXiv Feb 2, 2026
Continuous Conditional Diffusion Model (CCDM) is a diffusion-based framework designed to generate high-quality images conditioned on continuous regression labels. Although CCDM has demonstrated clear advantages over prior approaches across a range of... read more 
Computer Vision and Pattern Recognition cs.LG

FSVideo: Fast Speed Video Diffusion Model in a Highly-Compressed Latent Space

arXiv Feb 2, 2026
We introduce FSVideo, a fast speed transformer-based image-to-video (I2V) diffusion framework. We build our framework on the following key components: 1.) a new video autoencoder with highly-compressed latent space ($64\times64\times4$ spatial-tempor... read more 
Computer Vision and Pattern Recognition

Multi-View Stenosis Classification Leveraging Transformer-Based Multiple-Instance Learning Using Real-World Clinical Data

arXiv Feb 2, 2026
Coronary artery stenosis is a leading cause of cardiovascular disease, diagnosed by analyzing the coronary arteries from multiple angiography views. Although numerous deep-learning models have been proposed for stenosis detection from a single angiog... read more 
Computer Vision and Pattern Recognition cs.AI

FiLoRA: Focus-and-Ignore LoRA for Controllable Feature Reliance

arXiv Feb 2, 2026
Multimodal foundation models integrate heterogeneous signals across modalities, yet it remains poorly understood how their predictions depend on specific internal feature groups and whether such reliance can be deliberately controlled. Existing studi... read more 
Machine Learning cs.AI
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