Artificial Intelligence Medical Compendium

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

Showing 1 to 10 of 212,168 articles

Translational gaps and clinical readiness of artificial intelligence and multimodal imaging in breast cancer diagnostics.

Discover oncology Jul 19, 2026
BACKGROUND: A persistent translational gap separates the high research-benchmark performance of artificial intelligence (AI) and advanced imaging in breast cancer from demonstrated real-world clinical utility. Most systems reporting accuracy above 95... read more 

Advancing FAIR data towards comparable, organized, predictive AI-ready data for community validation.

Communications biology Jul 18, 2026
The interrogation of data across biological and environmental systems has become increasingly complex. Fortunately, communities are adopting the FAIR (Findable, Accessible, Interoperable, Reusable) data principles for individual datasets, and continu... read more 

Integrating single-cell sQTL mapping with deep-learning splicing prediction identifies causal variants under influenza infection.

Genome biology Jul 18, 2026
BACKGROUND: Realizing the full potential of human genetics requires identifying causal variants and genes underlying association signals. Molecular quantitative trait locus (molQTL) analyses, such as expression QTL (eQTL) and splicing QTL (sQTL), lin... read more 

Translational gaps and clinical readiness of artificial intelligence and multimodal imaging in breast cancer diagnostics.

Discover oncology Jul 19, 2026
BACKGROUND: A persistent translational gap separates the high research-benchmark performance of artificial intelligence (AI) and advanced imaging in breast cancer from demonstrated real-world clinical utility. Most systems reporting accuracy above 95... read more 

Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards.

Scientific reports Jul 19, 2026
We report a multimodal graph-based deep learning framework that integrates molecular graph topology with physicochemical descriptors to predict the heat of combustion (HoC) directly from chemical structure. The model employs a neural network convolut... read more 

Learning ordinality-aware multimodal representations for composite materials design.

Nature communications Jul 18, 2026
Composite materials design requires understanding complex microstructural characteristics, necessitating the integration of heterogeneous data sources with artificial intelligence. Current multimodal learning frameworks are mostly developed for cryst... read more 

Model Development and Feasibility of Real-World Deployment of Multimodal Input-Based Subtyping of Depression in Tele-Counseling for Scalable Mental Health Assessment.

Bio Systems Jul 18, 2026
The rapid growth of tele-counseling and the use of lay counselors in high-volume, low-resource mental health services has created a need for scalable tools for early detection and triage. Effective personalization now requires stratifying individuals... read more 

Utilizing Large Language Models to Enhance Patient-Reported Outcome Measures: Application to the EQ-5D-5L and Bolt-ons.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Jul 18, 2026
OBJECTIVES: Large language models (LLMs) may be useful tools for the development/adaptation of patient-reported outcome measures (PROMs). As a methodological proof-of-concept, we evaluated the use of LLMs to support the identification of potential EQ... read more 

WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion.

Ultrasound in medicine & biology Jul 18, 2026
OBJECTIVE: Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or magnetic resonance imaging (MRI), using electromagnetic (EM) tracking to enable precise spatial corr... read more 

WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion.

Ultrasound in medicine & biology Jul 18, 2026
OBJECTIVE: Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or magnetic resonance imaging (MRI), using electromagnetic (EM) tracking to enable precise spatial corr... read more 
Popular Topics
Recent Journals