Artificial Intelligence Medical Compendium

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

Showing 62,781 to 62,790 of 230,507 articles

Digital FAST: An AI-Driven Multimodal Framework for Rapid and Early Stroke Screening

arXiv
Early identification of stroke symptoms is essential for enabling timely intervention and improving patient outcomes, particularly in prehospital settings. This study presents a fast, non-invasive multimodal deep learning framework for automatic bina... read more 

Accelerated MR Elastography Using Learned Neural Network Representation

arXiv
To develop a deep-learning method for achieving fast high-resolution MR elastography from highly undersampled data without the need of high-quality training dataset. We first framed the deep neural network representation as a nonlinear extension of t... read more 

Adversarial Drift-Aware Predictive Transfer: Toward Durable Clinical AI

arXiv
Clinical AI systems frequently suffer performance decay post-deployment due to temporal data shifts, such as evolving populations, diagnostic coding updates (e.g., ICD-9 to ICD-10), and systemic shocks like the COVID-19 pandemic. Addressing this ``ag... read more 

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord.

Medical image analysis
T2 hyperintensities in spinal cord MR images are crucial biomarkers for conditions such as degenerative cervical myelopathy (DCM). However, current clinical diagnoses primarily rely on manual evaluation. Deep learning methods have shown promise in le... read more 

Beyond binary diagnosis: Key questions on AI accuracy, real-world applicability, and safety in clinical decision support.

International journal of medical informatics
This comment relates to Kücking et al.'s (2026) study on the bidirectional effects of artificial intelligence recommendations and healthcare provider related factors on the accuracy of wound impregnation diagnosis. While acknowledging the valuable co... read more 

Token-Level Attribution for Transparent Biomedical AI.

Biomedical engineering and computational biology
BACKGROUND: Explainability (xAI) is critical for fostering trust, ensuring safety, and supporting regulatory compliance in healthcare AI systems. Large Language Models (LLMs), with impressive capabilities, operate as "black boxes" with prohibitive co... read more 

Associations of blood cell indices with the severity of rheumatoid arthritis: a retrospective case-control and machine learning modeling study.

Therapeutic advances in musculoskeletal disease
BACKGROUND: Immune cells are involved in rheumatoid arthritis (RA), but the link between other blood cell indices and the disease activity of RA, along with the underlying mechanisms, is unclear. OBJECTIVE: This study aimed to develop an interpretabl... read more 

Deep learning for depression prediction in older adults: A retrospective cohort study from CHARLS (2011-2020) with independent cohort validation in CLHLS (2008-2018).

Journal of affective disorders
BACKGROUND: Geriatric depression is highly prevalent yet under-recognized, severely affecting older adults' quality of life and social functioning. There is an urgent need for individualized early prediction tools. While deep learning (DL) holds pote... read more 

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation.

Journal of advanced research
INTRODUCTION: Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often adapted from animal studies and perform sub-optimally on plant data. The lack of plant-specific com... read more