Artificial Intelligence Medical Compendium

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

Showing 37,871 to 37,880 of 223,469 articles

Deep Learning for scaling large-aperture photoacoustic computed tomography : From single fingers to the human hand.

Ultrasonics Mar 27, 2026
Photoacoustic Computed Tomography (PACT) leverages the photoacoustic effect for high-resolution anatomical and molecular imaging. We developed an advanced PACT system using eight conventional linear arrays arranged in a half-ring geometry, achieving ... read more 

Deep transfer learning radiomics combined with explainable machine learning for predicting malignancy risk in parotid gland tumors based on ultrasound.

European journal of radiology Mar 27, 2026
OBJECTIVE: This study aimed to develop and validate an ultrasound (US)-based deep transfer learning radiomics model, integrated with explainable machine learning, for the preoperative malignant risk prediction of parotid gland tumors (PGTs). METHODS:... read more 

Introduction to secure data sharing in primary care using the federated causal learning models.

BMJ health & care informatics Mar 27, 2026
OBJECTIVES: In primary healthcare research, there are core challenges such as data silos and missing data. Furthermore, the current high technical barriers severely limit effective cross-regional data analysis. METHODS: This work was the first to app... read more 

Novel two-stage deep learning framework for automated pressure injury classification.

BMJ health & care informatics Mar 27, 2026
OBJECTIVE: The study aims to develop an artificial intelligence (AI) framework for automatic pressure injury (PI) staging directly from raw clinical images, without requiring manual lesion localisation. By integrating a two-stage deep learning approa... read more 

Biomarkers associated with future suicide risk enhance predictive performance in psychiatric inpatients.

BMJ health & care informatics Mar 27, 2026
OBJECTIVES: Suicide risk assessments currently rely on subjective clinical judgement, lacking objective measures. This study aimed to evaluate the association between biomarkers and suicide risk and to explore their predictive potential using machine... read more 

On the relationships between apathy, depression and anhedonia.

Journal of neurology, neurosurgery, and psychiatry Mar 27, 2026
BACKGROUND: Apathy, depression and anhedonia are clinically overlapping constructs, which hinders diagnostic clarity and treatment development. This study aimed to comprehensively characterise these syndromes to identify a core set of non-redundant s... read more 

Impact of an artificial intelligence-driven triage system on workflow and transfer efficiency: stratified analysis of 4548 admissions to four thrombectomy hubs receiving transfers from sixty spokes.

Journal of neurology, neurosurgery, and psychiatry Mar 27, 2026
BACKGROUND: We aimed to evaluate the impact of implementing an artificial intelligence (AI)-enabled acute ischaemic stroke triage system on workflow efficiency and transfer optimisation in a large academic healthcare network. METHODS: A prospectively... read more 

Parvalbumin Neuron-Targeted Loss of Alzheimer's Disease Risk Gene BIN1 Is Insufficient to Drive Cognitive or Network Excitability Changes.

eNeuro Mar 27, 2026
Bridging integrator 1 (BIN1) is one of the strongest genetic risk factors for Alzheimer's disease (AD), yet its function in the brain and role in AD remain unclear. Neuronal BIN1 isoform levels are decreased in AD, and recent data show an important r... read more 

Hypergraph Representations of Single-Cell RNA Sequencing Data for Improved Cell Clustering.

Bioinformatics (Oxford, England) Mar 27, 2026
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. These network-based algorithms are attractive because regulatory interactions are fundamentally network... read more 

SMART: spatial multi-omic aggregation using graph neural networks and metric learning.

Nature communications Mar 27, 2026
Spatial multi-omics enables the exploration of tissue microenvironments and heterogeneity from the perspective of different omics modalities across distinct spatial domains within tissues. To jointly analyze the spatial multi-omics data, computationa... read more 
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