Using data mining to predict success in a weight loss trial-Reference-Cited by-同舟云学术

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Using data mining to predict success in a weight loss trial

Published:2017-02-07 Issue:4 Volume:30 Page:471-478
ISSN:0952-3871
Container-title:Journal of Human Nutrition and Dietetics
language:en
Short-container-title:J Hum Nutr Diet

Author:

Batterham M.¹,Tapsell L.²,Charlton K.³,O'Shea J.³,Thorne R.³

Affiliation:

1. Statistical Consulting Centre; National Institute for Applied Statistical Research Australia; University of Wollongong; Wollongong NSW Australia

2. Nutrition and Dietetics; School of Medicine; Faculty of Science Medicine and Health; University of Wollongong; Wollongong NSW Australia

3. School of Medicine; Faculty of Science, Medicine and Health; University of Wollongong; Wollongong NSW Australia

Funder

Horticulture Australia

Department of Agriculture, Australian Government

Publisher

Wiley

Subject

Nutrition and Dietetics,Medicine (miscellaneous)

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jhn.12448/fullpdf

Reference42 articles.

1. Predictors of attrition and weight loss success: results from a randomized controlled trial;Fabricatore;Behav Res Ther,2009

2. Initial weight loss is the best predictor for success in obesity treatment and sociodemographic liabilities increase risk for drop-out;Elfhag;Patient Educ Couns,2010

3. Factors predictive of drop-out and weight loss success in weight management of obese patients;Ortner Hadziabdic;J Hum Nutr Diet,2015

4. Predictors of programme adherence and weight loss in women in an obesity programme using meal replacements;Packianathan;Diabetes Obes Metab,2005

5. A simple model predicting individual weight change in humans;Thomas;J Biol Dyn,2011

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1. Weight Loss Trajectories and Short-Term Prediction in an Online Weight Management Program;Nutrients;2024-04-19

2. Importance of early weight loss and other predictors of lower weight loss in a commercial program: A secondary data analysis;Obesity Science & Practice;2023-11-30

3. Development and validation of a weight-loss predictor to assist weight loss management;Scientific Reports;2023-11-24

4. Effect of CoSn3 nanocrystals on Sn3Ag plating for electronic packaging;Scientific Reports;2023-11-24

5. A review of the application of machine learning in adult obesity studies;Applied Computing and Intelligence;2022

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