AIMC Topic: Humans

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Improved 3D DESS MR neurography of the lumbosacral plexus with deep learning and geometric image combination reconstruction.

Skeletal radiology
OBJECTIVE: To evaluate the impact of deep learning (DL) reconstruction in enhancing image quality and nerve conspicuity in LSP MRN using DESS sequences. Additionally, a geometric image combination (GIC) method to improve DESS signals' combination was...

Stop moving: MR motion correction as an opportunity for artificial intelligence.

Magma (New York, N.Y.)
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image quality. Various prospective and retrospective methods have been proposed for MRI motion correction, among which deep learning ap...

Opening Pandora's box by generating ICU diaries through artificial intelligence: A hypothetical study protocol.

Intensive & critical care nursing
BACKGROUND: Patients and families on Intensive Care Units (ICU) benefit from ICU diaries, enhancing their coping and understanding of their experiences. Staff shortages and a limited amount of time severely restrict the application of ICU diaries. To...

Aorta Segmentation in 3D CT Images by Combining Image Processing and Machine Learning Techniques.

Cardiovascular engineering and technology
PURPOSE: Aorta segmentation is extremely useful in clinical practice, allowing the diagnosis of numerous pathologies, such as dissections, aneurysms and occlusive disease. In such cases, image segmentation is prerequisite for applying diagnostic algo...

Exploring the impact of socially assistive robots on health and wellbeing across the lifespan: An umbrella review and meta-analysis.

International journal of nursing studies
BACKGROUND: Socially assistive robots offer an alternate source of connection for interventions within health and social care amidst a landscape of technological advancement and reduced staff capacity. There is a need to summarise the available syste...

Machine learning-based identification and characterization of mast cells in eosinophilic esophagitis.

The Journal of allergy and clinical immunology
BACKGROUND: Eosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.

Deep learning model for the detection of prostate cancer and classification of clinically significant disease using multiparametric MRI in comparison to PI-RADs score.

Urologic oncology
BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) is an established reporting scheme for multiparametric magnetic resonance imaging (mpMRI) to distinguish clinically significant prostate cancer (csPCa). Deep learning (DL) holds gre...

Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm.

World neurosurgery
OBJECTIVE: The significance of noncontrast computer tomography (CT) image markers in predicting hematoma expansion (HE) following intracerebral hemorrhage (ICH) within different time intervals in the initial 24 hours after onset may be uncertain. Hen...

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.

Molecular informatics
Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spread of AMR and associated mortality, methods for rapid selection of optimal antibiotic treatment are urgently needed. Machine learning (ML) models bas...