Last Posted: Jul 13, 2021
- Predicting Obesity in Adults Using Machine Learning Techniques: An Analysis of Indonesian Basic Health Research 2018.
Thamrin Sri Astuti et al. Frontiers in nutrition 2021 8669155
- The association of a novel digital tool for assessment of early childhood cognitive development, 'DEvelopmental assessment on an E-Platform (DEEP)', with growth in rural India: A proof of concept study.
Bhavnani Supriya et al. EClinicalMedicine 2021 37100964
- Discovery of Depression-Associated Factors From a Nationwide Population-Based Survey: Epidemiological Study Using Machine Learning and Network Analysis.
Nam Sang Min et al. Journal of medical Internet research 2021 23(6) e27344
- Meta-analysis and machine learning-augmented mixed effects cohort analysis of improved diets among 5,847 medical trainees, providers, and patients.
Monlezun Dominique J et al. Public health nutrition 2021 1-27
- Exploring the evidence for epigenetic regulation of environmental influences on child health across generations.
Breton Carrie V et al. Communications biology 2021 4(1) 769
- Maternal Factors Predicting Loss to Follow-Up from Newborn Hearing Screenings in New Jersey.
Zeitlin Wendy et al. Health & social work 2021 46(2) 115-124
- An Automated Machine Learning Classifier for Early Childhood Caries.
Karhade Deepti S et al. Pediatric dentistry 2021 43(3) 191-197
- Predictors of tooth loss: A machine learning approach.
Elani Hawazin W et al. PloS one 2021 16(6) e0252873
- The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition.
Limketkai Berkeley N et al. Current surgery reports 2021 9(7) 20
- Change in Nutrient and Dietary Intake in European Children with Cystic Fibrosis after a 6-Month Intervention with a Self-Management mHealth Tool.
Calvo-Lerma Joaquim et al. Nutrients 2021 13(6)
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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.