Artificial Intelligence Medical Compendium

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

Showing 18,701 to 18,710 of 214,544 articles

MiVE: Multiscale Vision-language features for reference-guided video Editing

arXiv May 14, 2026
Reference-guided video editing takes a source video, a text instruction, and a reference image as inputs, requiring the model to faithfully apply the instructed edits while preserving original motion and unedited content. Existing methods fall into t... read more 
Computer Vision and Pattern Recognition

EponaV2: Driving World Model with Comprehensive Future Reasoning

arXiv May 14, 2026
Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving relies heavily on expensive manual annotations to supervise trajectory planning, which severely limit... read more 
Computer Vision and Pattern Recognition

NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces

arXiv May 14, 2026
Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including electroencephalography (EEG), but it is less clear how effective they are in this particular field.... read more 
Machine Learning cs.AI

Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners

arXiv May 14, 2026
Recent unified models integrate multimodal understanding and generation within a single framework. However, an "understanding-generation gap" persists, where models can capture user intent but often fail to translate this semantic knowledge into prec... read more 
Computer Vision and Pattern Recognition

Vision-Core Guided Contrastive Learning for Balanced Multi-modal Prognosis Prediction of Stroke

arXiv May 14, 2026
Deep learning and multi-modal fusion have demonstrated transformative potential in medical diagnosis by integrating diverse data sources. However, accurate prognosis for ischemic stroke remains challenging due to limitations in existing multi-modal a... read more 
Computer Vision and Pattern Recognition cs.AI

Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning

arXiv May 14, 2026
Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cytometry, yet inferring molecular phenotypes directly from bright-field morphology remains challenging. We present a unified Deep Learning (DL) framewor... read more 
Computer Vision and Pattern Recognition cs.AI

Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model

arXiv May 14, 2026
Sepsis management in the ICU requires sequential treatment decisions under rapidly evolving patient physiology. Although large language models (LLMs) encode broad clinical knowledge and can reason over guidelines, they are not inherently grounded in ... read more 
Artificial Intelligence cs.CL cs.LG

CHASM: Cross-frequency Harmonized Axis-Separable Mixing for Spectral Token Operators

arXiv May 14, 2026
Spectral token mixers based on Fourier transforms provide an efficient way to model global interactions in visual feature maps. Existing designs often either apply filter-wise spectral responses along fixed channel axes, or learn adaptive frequency-i... read more 
Computer Vision and Pattern Recognition

Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement

arXiv May 14, 2026
De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative models are trained to maximize the likelihood of observed crystals, which encourages samples to stay cl... read more 
Machine Learning

AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction

arXiv May 14, 2026
Accurately predicting individual aesthetic evaluation for images is a fundamental challenge for AI. Various deep learning (DL)-based models have been proposed for this task, training on image evaluation data to extract objective low-level features. H... read more 
Artificial Intelligence cs.HC
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