Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature
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Summary
This review has found that CDS tools can be useful for the self-management or remote medical management of childhood obesity, whereas ML algorithms such as decision trees and artificial neural networks can be helpful for prediction purposes.
- Type
- review
- Published
- 2020-03-19
- Cited by
- 57
- References
- 66
- OpenAlex
- https://openalex.org/W3011069322
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:215919309
Keywords
Computer science, Childhood obesity, Systematic review, Decision support system, Artificial intelligence
References
- Impact of Electronic Health Record Clinical Decision Support on the Management of Pediatric Obesity
- Predicting the Future — Big Data, Machine Learning, and Clinical Medicine
- Abdominal obesity and cardiovascular disease risk factors within body mass index categories.
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Development and Implementation of an Interactive Text Messaging Campaign to Support Behavior Change in a Childhood Obesity Randomized Controlled Trial
- Improving children's obesity‐related health care quality: Process outcomes of a cluster‐randomized controlled trial
- Validation of a Food Frequency Questionnaire in Native American and Caucasian Children 1 to 5 Years of Age
- The use of measures of obesity in childhood for predicting obesity and the development of obesity-related diseases in adulthood: a systematic review and meta-analysis.
- Applications of Machine Learning in Cancer Prediction and Prognosis
- Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach
- Prevention and treatment of pediatric obesity using mobile and wireless technologies: a systematic review
- Identifying patterns of obesity risk behavior to improve pediatric primary care.
- Feasibility Study of a Sensor-Based Autonomous Load Control Exercise Training System for COPD Patients
- mHealth approaches to child obesity prevention: successes, unique challenges, and next directions
- Active Video Games and Health Indicators in Children and Youth: A Systematic Review
- Comparison of self-reported versus accelerometer-measured physical activity.
- Exergaming as a Strategic Tool in the Fight against Childhood Obesity: A Systematic Review
- Using Active Video Games for Physical Activity Promotion
- Zotero: A bibliographic assistant to researcher
- Multifactorial intervention in diabetes care using real-time monitoring and tailored feedback in type 2 diabetes
Cited by
- Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review
- A Social Robot-based Platform towards Automated Diet Tracking
- Harnessing technological solutions for childhood obesity prevention and treatment: a systematic review and meta-analysis of current applications
- The Prediction of Body Mass Index from Negative Affectivity through Machine Learning: A Confirmatory Study
- Insulin Resistance in Obese Children and Adolescents in Relation to Breastfeeding Duration
- Prediction of early childhood obesity with machine learning and electronic health record data
- Effect of Mobile Health Technology on Weight Control in Adolescents and Preteens: A Systematic Review and Meta-Analysis
- The BAriatic surgery SUbstitution and nutrition (BASUN) population: a data-driven exploration of predictors for obesity
- A Survey on Machine and Deep Learning Models for Childhood and Adolescent Obesity
- Application of artificial intelligence in clinical diagnosis and treatment: an overview of systematic reviews
- Digital health for quality healthcare: A systematic mapping of review studies
- Efficacy of Emerging Technologies to Manage Childhood Obesity
- Dependence of Body Mass Index on Some Dietary Habits: An Application of Classification and Regression Tree
- Design and Application of Preschool Education System Based on Mobile Application
- Applications of Machine Learning Models to Predict and Prevent Obesity: A Mini-Review
- The Potential Role of Digital Health in Obesity Care
- A social robot-based platform for health behavior change toward prevention of childhood obesity
- Perspectives of telemedicine technologies in the treatment of overweight and obesity
- The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity
- Predicting body mass index in early childhood using data from the first 1000 days
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