Artificial Intelligence Medical Compendium

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

Showing 30,591 to 30,600 of 220,100 articles

Federated learning's uncomfortable truth: why human networks matter more than neural networks.

Journal of the American Medical Informatics Association : JAMIA Apr 15, 2026
OBJECTIVES: To examine real-world barriers to implementing federated learning in healthcare and highlight the organizational, regulatory, and socio-technical factors often overlooked in technical research. MATERIALS AND METHODS: Insights were derived... read more 

D-Flow: Multi-modality Flow Matching for D-peptide Design.

IEEE journal of biomedical and health informatics Apr 15, 2026
Proteins are crucial to biological processes, and therapeutic peptides are emerging as promising pharmaceutical agents. Among these, D-peptides are resistant to proteolysis, exhibit greater in vivo stability, and are easier to synthesize. Despite adv... read more 

BLADE: Breast Lesion Analysis with Domain Expertise for DCE-MRI Diagnosis.

IEEE journal of biomedical and health informatics Apr 15, 2026
Dynamic Contrast-Enhanced Magnetic Reso nance Imaging (DCE-MRI) is pivotal in breast cancer diag nosis, yet radiologists face challenges in interpreting its complex data due to the lack of robust automated tools. Current lesion diagnosis systems stru... read more 

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

IEEE journal of biomedical and health informatics Apr 15, 2026
Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantitative characterization of fibrosis-related tissue changes across the whole liver. Although deep-lear... read more 

Public Perceptions of AI in Medicine and Implications for Future Medical Education: Cross-Sectional Survey.

JMIR formative research Apr 15, 2026
BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physician oversight, yet a significant gap exists between the need for AI-competent physicians and the curre... read more 

A Preliminary Study of a Machine Learning Prediction of Poorly Differentiated Hepatocellular Carcinoma Based on a Comprehensive Parameter Analysis Using Dual-Energy Computed Tomography.

Journal of computer assisted tomography Apr 15, 2026
OBJECTIVE: To develop and evaluate the performance of a predictive machine learning model for poorly differentiated hepatocellular carcinoma (p-HCC) using comprehensive quantitative parameters from dual-energy computed tomography (DECT). MATERIALS AN... read more 

Development of a Contextualized, Research-Based Flemish Assessment Framework for Digital Care, Assistance, and Support: Delphi Study.

JMIR formative research Apr 15, 2026
BACKGROUND: The rapid evolution of digital technologies has transformed health, mental health, and social care, offering new modalities of digital care, assistance, and support through web-based platforms, mobile apps, extended reality, wearables, an... read more 

Sustainable Materials Design With Multi-Modal Artificial Intelligence.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 15, 2026
The growing scarcity of critical minerals, coupled with high embodied carbon emissions and persistent pollution from material smelting, highlights the urgent need for a sustainable transformation in materials design. This challenge can be approached ... read more 

Machine-Learning Microfluidic Minute-Scale Microorganism Metrics Monitoring(M6).

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 15, 2026
On-site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol-transmitted pathogens. Here, we report a rapid detection platform that int... read more 

A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.

Journal of medical engineering & technology Apr 15, 2026
Automated segmentation of kidney tumors from computed tomography (CT) scans is crit- ical for diagnosis, treatment planning, and monitoring of renal cell carcinoma (RCC). While recent deep learning models report high Dice scores (>0.97), their clinic... read more 
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