AIMC Topic: Cross-Sectional Studies
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Profiling movement behaviours in pre-school children: A self-organised map approach.
Journal of sports sciences
Nov 7, 2019
Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours and tangible profiles. The aim of this study was to identify profiles of relative motor competence (MC...
A network perspective on body dysmorphic disorder and major depressive disorder.
Journal of affective disorders
Nov 5, 2019
BACKGROUND: Body dysmorphic disorder (BDD) is a highly debilitating mental disorder associated with notable psychosocial impairment and high rates of suicidality. This study investigated BDD from a network perspective, which conceptualizes mental dis...
Predicting skilled delivery service use in Ethiopia: dual application of logistic regression and machine learning algorithms.
BMC medical informatics and decision making
Nov 5, 2019
BACKGROUND: Skilled assistance during childbirth is essential to reduce maternal deaths. However, in Ethiopia, which is among the six countries contributing to more than half of the global maternal deaths, the coverage of births attended by skilled h...
Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine.
International journal of environmental research and public health
Nov 3, 2019
This study developed a support vector machine (SVM) algorithm-based prediction model with considering influence factors associated with the swallowing quality-of-life as the predictor variables and provided baseline information for enhancing the swa...
Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter.
JAMA network open
Nov 1, 2019
IMPORTANCE: Automatic curation of consumer-generated, opioid-related social media big data may enable real-time monitoring of the opioid epidemic in the United States.
A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.
Journal of sports sciences
Oct 28, 2019
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...
Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study.
Journal of medical Internet research
Oct 17, 2019
BACKGROUND: Poor quality primary health care is a major issue in China, particularly in blindness prevention. Artificial intelligence (AI) could provide early screening and accurate auxiliary diagnosis to improve primary care services and reduce unne...
Development of a clinical support system for identifying social frailty.
International journal of medical informatics
Sep 26, 2019
OBJECTIVE: Recognizing frailty, also known as clinical geriatric syndrome in the elderly that is characterized by high vulnerability and low resilience, and its extensive influence in clinical practice is challenging. This study aims to develop a soc...
The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.
Topics in stroke rehabilitation
Sep 4, 2019
: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing and stance stability, which make it possible to practice walking without excessive compensation move...
Comparison between logistic regression and machine learning algorithms on survival prediction of traumatic brain injuries.
Journal of critical care
Aug 5, 2019
PURPOSE: To compare twenty-two machine learning (ML) models against logistic regression on survival prediction in severe traumatic brain injury (STBI) patients in a single center study.
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