Artificial Intelligence Medical Compendium

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

Showing 14,071 to 14,080 of 211,462 articles

Learning Emergent Modular Representations in Multi-modality Medical Vision Foundation Models

arXiv
Multi-modality medical vision (MV) foundation models (FM) are fundamentally challenged by pronounced Non-IID feature statistics across heterogeneous imaging modalities. Monolithic self-supervised optimization on such data induces conflicting gradient... read more 

Thermo-VL: Extending Vision-Language Models to Thermal Infrared Perception

arXiv
Vision-language models (VLMs) often fail under low illumination because their visual grounding is learned predominantly from RGB imagery, whereas thermal infrared preserves complementary scene structure when visible cues degrade. We present Thermo-VL... read more 

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining

arXiv
Computed tomography (CT) is a central to three-dimensional medical imaging, yet CT-based artificial intelligence remains fragmented across task-specific models for segmentation, classification, registration, and report analysis. Here we present Flexi... read more 

Guided Trajectory Optimization with Sparse Scaling for Test-Time Diffusion

arXiv
The efficient Test-Time Scaling (TTS) paradigm offers a promising perspective for enhancing the generation performance of diffusion models. However, current solutions are limited to a static, pre-defined noise pool and suffer from inflexible noise ex... read more 

Noise Schedule Design for Diffusion Models: An Optimal Control Perspective

arXiv
We develop a principled framework for analyzing and designing noise schedules in diffusion models. We show that one can recast this design problem as an optimal control problem, whose state is the Fisher information of the diffusion process which evo... read more 

Multi-scale interaction network for stereo image super-resolution

arXiv
Stereo image super-resolution aims to generate high-resolution images by leveraging complementary information from binocular systems. Although previous studies have achieved impressive results, the potential of intra-view and cross-view information h... read more 

EvoVid: Temporal-Centric Self-Evolution for Video Large Language Models

arXiv
Recent Video Large Language Models (Video-LLMs) have demonstrated strong capabilities in video reasoning through reinforcement learning (RL). However, existing RL pipelines rely heavily on human-annotated tasks and solutions, making them costly to sc... read more 

ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data

arXiv
Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-disease care, yet existing electronic health record (EHR) models are predominantly discriminative, and... read more 

Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detection

arXiv
Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strategies compress the reconstructio... read more 

Entropy-Guided Self-Supervised Learning for Medical Image Classification

arXiv
Accurate and robust medical image classification is paramount for early disease diagnosis and treatment planning. However, challenges such as limited annotated data, high intra-class variability, and subtle inter-class differences often hinder the pe... read more