Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature
作者：
Highlights：
• Computerized decision support interventions for childhood obesity were found to be useful for children and their carers.
• Machine learning techniques have been found to generate useful knowledge to predict (mainly) or diagnose childhood obesity.
• The integration of machine learning algorithms into electronic tools, is needed to develop smart and impactful digital health interventions.
• Further rigorous studies in the area of computerized decision support and machine learning applications for childhood obesity care are needed.
摘要
•Computerized decision support interventions for childhood obesity were found to be useful for children and their carers.•Machine learning techniques have been found to generate useful knowledge to predict (mainly) or diagnose childhood obesity.•The integration of machine learning algorithms into electronic tools, is needed to develop smart and impactful digital health interventions.•Further rigorous studies in the area of computerized decision support and machine learning applications for childhood obesity care are needed.
论文关键词：Childhood obesity,Computerized decision support,Machine learning,Digital health,Review
论文评审过程：Received 29 August 2019, Revised 9 March 2020, Accepted 12 March 2020, Available online 19 March 2020, Version of Record 19 March 2020.
论文官网地址：https://doi.org/10.1016/j.artmed.2020.101844
