Artificial Intelligence Medical Compendium

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

Showing 11,901 to 11,910 of 210,187 articles

Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models

arXiv May 25, 2026
Concept unlearning aims to erase a target concept from a pretrained text-to-image diffusion model without retraining. Closed-form methods are attractive in this setting because they apply a single deterministic edit to the cross-attention weights and... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

SAFE-Diff: Scale-Aware Attention and Feature-Dispersive Diffusion with Uncertainty Estimation for Contrast-Enhanced Breast MRI Synthesis

arXiv May 25, 2026
Synthesizing high fidelity contrast enhanced MRI is clinically valuable for safer and more efficient breast cancer screening, yet remains challenging due to complex lesion textures and heterogeneous enhancement patterns. read more 
Computer Vision and Pattern Recognition

OMGTex: One-stage Multi-style Facial Texture Reconstruction without Geometry Guidance

arXiv May 25, 2026
We propose OMGTex, an end-to-end diffusion-based framework for reconstructing high-quality and editable facial UV textures from multi-style facial images. Existing texture reconstruction methods face two major limitations: (1) Fragility due to relian... read more 
Computer Vision and Pattern Recognition

Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models

arXiv May 25, 2026
Diffusion-based multimodal large language models (dMLLMs) decode by iteratively predicting tokens at multiple masked positions in parallel. This turns each decoding step into a position-selection problem: the model must choose not only which predicti... read more 
Machine Learning

[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation

arXiv May 25, 2026
Vision-Language Models such as CLIP exhibit strong zero-shot recognition capability by aligning images with textual concepts, yet they often underperform on multi-label recognition where multiple objects co-exist. A key bottleneck is that the [CLS] t... read more 
Computer Vision and Pattern Recognition

Artificial intelligence in food technology and processing: a review.

Journal of food science and technology May 25, 2026
UNLABELLED: The food industry faces numerous challenges, including ensuring food safety, managing supply chain disruptions, meeting changing consumer demands, addressing climate change impacts, and reducing food waste. Artificial Intelligence (AI) of... read more 

Normative modeling for quantitative brain MRI phenotyping and biomarker discovery for pediatric leukodystrophies

medRxiv May 25, 2026
Importance: Leukodystrophies are a heterogeneous group of genetic disorders affecting the white matter of the brain, often presenting with overlapping clinical features but differing in neuroanatomical involvement. There is a critical need for quanti... read more 
neurology

Assessing Foundation Models for Computational Pathology in Endometrial Cancer

medRxiv May 25, 2026
Computational pathology leverages deep learning to extract clinically relevant information from digitized tumor slides, predicting histopathological subtypes, molecular alterations, and patient outcomes. Recent pipelines increasingly rely on foundati... read more 
pathology

Cross-Model Variability in Large Language Model Triage Behavior for Potential Stroke Symptoms

medRxiv May 25, 2026
Background: Stroke is a time-sensitive neurological emergency in which early EMS activation and presentation to definitive care are cornerstones of effective therapy. Large language models (LLMs) are increasingly consulted by the public for medical a... read more 
emergency medicine

Cumulative In-Context Learning versus Simple Historical Weighting for Real-Time Geographic Origin Identification of Ongoing Epidemic Waves: A Comparative Evaluation Using Eight COVID-19 Waves in Japan

medRxiv May 25, 2026
Background: Identifying the geographic origin of epidemic waves early is critical for targeted public health responses. Conventional statistical methods for wave origin estimation rely on fixed algorithms applied to case count time-series data and tr... read more 
public and global health
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