Artificial Intelligence Medical Compendium

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

Showing 57,841 to 57,850 of 227,388 articles

Computational Framework for Estimating Relative Gaussian Blur Kernels between Image Pairs

arXiv
Following the earlier verification for Gaussian model in \cite{ASaa2026}, this paper introduces a zero training forward computational framework for the model to realize it in real time applications. The framework is based on discrete calculation of t... read more 

Spatial-Conditioned Reasoning in Long-Egocentric Videos

arXiv
Long-horizon egocentric video presents significant challenges for visual navigation due to viewpoint drift and the absence of persistent geometric context. Although recent vision-language models perform well on image and short-video reasoning, their ... read more 

GLEN-Bench: A Graph-Language based Benchmark for Nutritional Health

arXiv
Nutritional interventions are important for managing chronic health conditions, but current computational methods provide limited support for personalized dietary guidance. We identify three key gaps: (1) dietary pattern studies often ignore real-wor... read more 

LungCRCT: Causal Representation based Lung CT Processing for Lung Cancer Treatment

arXiv
Due to silence in early stages, lung cancer has been one of the most leading causes of mortality in cancer patients world-wide. Moreover, major symptoms of lung cancer are hard to differentiate with other respiratory disease symptoms such as COPD, fu... read more 

Nonlinear multi-study factor analysis

arXiv
High-dimensional data often exhibit variation that can be captured by lower dimensional factors. For high-dimensional data from multiple studies or environments, one goal is to understand which underlying factors are common to all studies, and which ... read more 

RareAlert: Aligning heterogeneous large language model reasoning for early rare disease risk screening

arXiv
Missed and delayed diagnosis remains a major challenge in rare disease care. At the initial clinical encounters, physicians assess rare disease risk using only limited information under high uncertainty. When high-risk patients are not recognised at ... read more 

EndoExtract: Co-Designing Structured Text Extraction from Endometriosis Ultrasound Reports

arXiv
Endometriosis ultrasound reports are often unstructured free-text documents that require manual abstraction for downstream tasks such as analytics, machine learning model training, and clinical auditing. We present \textbf{EndoExtract}, an on-premise... read more 

Multi-Perspective Subimage CLIP with Keyword Guidance for Remote Sensing Image-Text Retrieval

arXiv
Vision-Language Pre-training (VLP) models like CLIP have significantly advanced Remote Sensing Image-Text Retrieval (RSITR). However, existing methods predominantly rely on coarse-grained global alignment, which often overlooks the dense, multi-scale... read more 

PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR

arXiv
Search agents are language models (LMs) that reason and search knowledge bases (or the web) to answer questions; recent methods supervise only the final answer accuracy using reinforcement learning with verifiable rewards (RLVR). Most RLVR search age... read more 

Automated HER2 scoring with uncertainty quantification using lensfree holography and deep learning

arXiv
Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is critical for breast cancer diagnosis, prognosis, and therapy selection; yet, most existing digital HER2 scoring methods rely on bulky and expensive optical systems. ... read more