Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 22,971 to 22,980 of 216,842 articles
High-Resolution 2D versus 3D Lumbar Spine MRI Optimized with a Deep Learning Reconstruction Algorithm and Prototype Conformal Coil.
AJNR. American journal of neuroradiology
May 4, 2026
BACKGROUND AND PURPOSE: Lumbar spine MRI is predominantly performed using 2D FSE sequences. 3D FSE sequences offer potential advantages over 2D, especially with recent advances in deep-learning reconstruction (DLR) and the use of conformal high-densi... read more
Deep Learning Radiomics Signature from Multicontrast MRI for Automated Identification of Symptomatic Carotid Plaques: A Multicenter Study.
AJNR. American journal of neuroradiology
May 4, 2026
BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, beyond relying solely on stenosis degree, remains a critical challenge for precise stroke risk strat... read more
Understanding how language barriers in the paediatric emergency care setting influences safety of care delivery: a scoping review.
Emergency medicine journal : EMJ
May 4, 2026
BACKGROUND: Communication in a family's primary language can support safe care. Vital steps within the care delivery process are contingent on successful communication, including reporting symptoms, clinical decision-making, informed consent, dischar... read more
Mapping the body: poetic metaphor and AI imaging in Carol Ann Duffy's 'The Map-Woman'.
Medical humanities
May 4, 2026
This article offers an interdisciplinary analysis of Carol Ann Duffy's poem 'The Map-Woman', examining the metaphor of the female body as a map in relation to artificial intelligence (AI)-assisted medical imaging technologies. The study explores how ... read more
Cost savings and quality-of-life gains associated with the use of an AI-powered digital tool for self-management of chronic pain based on a multicenter cohort study.
Pain medicine (Malden, Mass.)
May 4, 2026
BACKGROUND: Chronic pain is a highly prevalent disease, leading to high health care costs, impaired productivity, and decreased quality of life. An artificial intelligence (AI)-powered, digital tool for self-management (PaindrainerTM) has been shown ... read more
Inverse theory of wavefront shaping in nonlinear scattering media.
Nature communications
May 4, 2026
Scattering fundamentally limits the propagation of light in complex media, yet controlling it is essential for transformative advances in imaging, sensing, and optical communication. While decades of research have established powerful methods for lin... read more
Polymer-free van der Waals assembly of 2D material heterostructures using muscovite crystals.
Nature communications
May 4, 2026
The advent of van der Waals (vdW) heterostructures has enabled formation of bespoke materials with atomic precision, where numerous quantum and topological phenomena have already been discovered. This atomic-layer tunability, however, comes at a cost... read more
Automated deep learning by recurrent hyperparameter optimization.
Nature communications
May 4, 2026
Optimizing hyperparameters of deep learning models for specific tasks requires substantial domain expertise and computational resources, remaining challenging in automated deep learning. Existing hyperparameter optimization (HPO) methods are restrict... read more
Mitigating algorithmic unfairness arising from forgetfulness of medical records in clinical artificial intelligence.
Nature communications
May 4, 2026
Protecting patients' right to be forgotten (RtbF) in the digital era underscores algorithms to delete health records from deployed artificial intelligence (AI) models upon requests, a paradigm also known as machine unlearning. Such forgetfulness, how... read more
Preparatory phase of large earthquakes illuminated by unsupervised categorization of earthquake catalog features.
Nature communications
May 4, 2026
Predicting large earthquakes remains a significant challenge due to the complexity of fault systems and the variability of preparatory processes. We introduce an unsupervised machine learning framework to categorize seismicity patterns and identify, ... read more
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