AIMC Topic: Adult

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Robot-assisted vs traditional percutaneous freehand for the scaphoid fracture treatment: a retrospective study.

International orthopaedics
PURPOSE: The purpose of this study was to assess the efficiency, safety, and accuracy of cannulated screw fixation using a robot-assisted method compared with a traditional percutaneous freehand method.

Deep learning reconstruction for the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI: comparison with 3T MRI without deep learning reconstruction.

Neuroradiology
PURPOSE: To compare image quality and interobserver agreement in evaluations of neuroforaminal stenosis between 1.5T cervical spine magnetic resonance imaging (MRI) with deep learning reconstruction (DLR) and 3T MRI without DLR.

A Questionnaire-Based Ensemble Learning Model to Predict the Diagnosis of Vertigo: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Questionnaires have been used in the past 2 decades to predict the diagnosis of vertigo and assist clinical decision-making. A questionnaire-based machine learning model is expected to improve the efficiency of diagnosis of vestibular dis...

Development and Validation of a Deep Learning Model for Brain Tumor Diagnosis and Classification Using Magnetic Resonance Imaging.

JAMA network open
IMPORTANCE: Deep learning may be able to use patient magnetic resonance imaging (MRI) data to aid in brain tumor classification and diagnosis.

Methodologies Used to Study the Feasibility, Usability, Efficacy, and Effectiveness of Social Robots For Elderly Adults: Scoping Review.

Journal of medical Internet research
BACKGROUND: New research fields to design social robots for older people are emerging. By providing support with communication and social interaction, these robots aim to increase quality of life. Because of the decline in functioning due to cognitiv...

Machine Learning-Based Prediction Models for Delirium: A Systematic Review and Meta-Analysis.

Journal of the American Medical Directors Association
OBJECTIVE: To critically appraise and quantify the performance studies by employing machine learning (ML) to predict delirium.

Artificial intelligence-based clinical decision support in pediatrics.

Pediatric research
Machine learning models may be integrated into clinical decision support (CDS) systems to identify children at risk of specific diagnoses or clinical deterioration to provide evidence-based recommendations. This use of artificial intelligence models ...

Deep learning to distinguish Best vitelliform macular dystrophy (BVMD) from adult-onset vitelliform macular degeneration (AVMD).

Scientific reports
Initial stages of Best vitelliform macular dystrophy (BVMD) and adult vitelliform macular dystrophy (AVMD) harbor similar blue autofluorescence (BAF) and optical coherence tomography (OCT) features. Nevertheless, BVMD is characterized by a worse fina...