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Two-step deep-learning identification of heel keypoints from video-recorded gait.

Medical & biological engineering & computing
Accurate and fast extraction of step parameters from video recordings of gait allows for richer information to be obtained from clinical tests such as Timed Up and Go. Current deep-learning methods are promising, but lack in accuracy for many clinica...

Non-traumatic brachial plexopathy identification from routine MRIs: Retrospective studies with deep learning networks.

European journal of radiology
PURPOSE: This study aims to seek an optimized deep learning model for differentiating non-traumatic brachial plexopathy from routine MRI scans.

Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models.

International journal of medical informatics
BACKGROUND: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generalizable machine learning (ML) al...

Electrocardiogram-Based Deep Learning to Predict Mortality in Repaired Tetralogy of Fallot.

JACC. Clinical electrophysiology
BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to predict mortality in adults with acquired cardiovascular diseases. However, its application to the growing repaired tetralogy of Fallot (rTOF) populatio...

DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.

Journal of forensic sciences
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...

Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa response (LR). Assessment of Movement Disorder Society's Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) is a key step in ALCT, which...

Development and validation of a machine learning-based framework for assessing metabolic-associated fatty liver disease risk.

BMC public health
BACKGROUND: The existing predictive models for metabolic-associated fatty liver disease (MAFLD) possess certain limitations that render them unsuitable for extensive population-wide screening. This study is founded upon population health examination ...

Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort.

BMC public health
BACKGROUND: Internet gaming disorder (IGD), recognized by the World Health Organization (WHO), significantly impacts adolescent mental and physical health. With a global prevalence of 3.05%, rates are higher in Asia, especially among adolescents and ...

Machine learning algorithm for predicting seizure control after temporal lobe resection using peri-ictal electroencephalography.

Scientific reports
Brain resection is curative for a subset of patients with drug resistant epilepsy but up to half will fail to achieve sustained seizure freedom in the long term. There is a critical need for accurate prediction tools to identify patients likely to ha...

Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.

JMIR mental health
BACKGROUND: The application of artificial intelligence (AI) to health and health care is rapidly increasing. Several studies have assessed the attitudes of health professionals, but far fewer studies have explored the perspectives of patients or the ...