Artificial Intelligence Medical Compendium

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

Showing 9,151 to 9,160 of 208,441 articles

Know when to trust: Making AI scoring more reliable for educational assessment.

Behavior research methods
The rapid rise of large language models (LLMs) has created new opportunities for educational measurement. This paper introduces and evaluates three improvements to LLM-based automated scoring tools: model self-confidence, weighted probabilistic scori... read more 

Artificial intelligence for gait and balance in neurological disorders: a scoping review of clinical applications and technologies.

Journal of neurology
BACKGROUND: Artificial intelligence (AI) has rapidly emerged within healthcare systems and neurological rehabilitation with the potential to revolutionize clinical decision-making and therapeutic strategies. However, a comprehensive understanding of ... read more 

Artificial intelligence-enabled plaque characterization from coronary computed tomography establishes basis of angina in women with nonobstructive atherosclerosis.

Communications medicine
BACKGROUND: Half of women with ischemic symptoms have non-obstructive coronary artery disease (CAD), while the pathophysiology of their condition has not been characterized. Noncalcified (NCP) and low-attenuation plaque (CT density<30 Hounsfield unit... read more 

Artificial intelligence and transforming cancer care.

Discover oncology
Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized approaches from diagnosis to treatment. This review explores the transformative role of AI across the c... read more 

Artificial intelligence in cancer immunotherapy: current trends in predicting response and personalizing treatment.

Journal of the Egyptian National Cancer Institute
Artificial intelligence (AI) can transform cancer immunotherapy by enabling more accurate prediction of treatment responses, the discovery of specific biomarkers, and the development of personalised treatment plans. Traditional single-marker biomarke... read more 

OpenRad: a curated repository of open-access AI models for radiology.

European radiology
OBJECTIVES: To create and evaluate OpenRad ( https://konstvr.github.io/OpenRad/index.html ), a curated, standardized repository that aggregates open-access radiology artificial intelligence (AI) models enriched with metadata from the corresponding co... read more 

VMAM-NET: A Model Agnostic Meta-Learning Network for Rare De Novo Glioblastoma Diagnosis.

Journal of imaging informatics in medicine
The diagnosis of grade IV brain tumors, such as de novo glioblastoma, has recently attracted a lot of scientific interest in neuroimaging and deep learning. Glioblastoma, a very rare and highly aggressive brain tumor, poses considerable diagnostic ch... read more 

Uncertainty-Aware Super-Resolution for Mammography Phantoms using a Dropout-Enabled SwinIR.

Journal of imaging informatics in medicine
This study was aimed at presenting a framework integrating uncertainty quantification into the SwinIR super-resolution model for mammography, addressing the "black box" limitation that hinders clinical trust. Monte Carlo (MC) Dropout was incorporated... read more 

FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation.

Nature computational science
Here we introduce FLOWR, a structure-based framework for the generation and optimization of three-dimensional ligands. FLOWR integrates continuous and categorical flow matching with equivariant optimal transport, enhanced by an efficient protein pock... read more 

Cross-material catalyst discovery via deep learning.

Nature materials
The discovery of catalysts is typically confined within individual material classes, limiting insight from across material types. Here we demonstrate a machine learning approach that bridges catalyst families by identifying co-descriptors derived fro... read more