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Citing this Article

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Published on 25.01.18 in Vol 6, No 1 (2018): January

This paper is in the following e-collection/theme issue:

Works citing "Evaluating Machine Learning–Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.9117):

(note that this is only a small subset of citations)

  1. Liu Y, Avello M. Status of the Research in Fitness Apps: A Bibliometric Analysis. Telematics and Informatics 2020;:101506
    CrossRef
  2. Ceasar JN, Claudel SE, Andrews MR, Tamura K, Mitchell V, Brooks AT, Dodge T, El-Toukhy S, Farmer N, Middleton K, Sabado-Liwag M, Troncoso M, Wallen GR, Powell-Wiley TM. Community Engagement in the Development of an mHealth-Enabled Physical Activity and Cardiovascular Health Intervention (Step It Up): Pilot Focus Group Study. JMIR Formative Research 2019;3(1):e10944
    CrossRef
  3. Milne-Ives M, Lam C, De Cock C, Van Velthoven MH, Meinert E. Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review. JMIR mHealth and uHealth 2020;8(3):e17046
    CrossRef
  4. Gasparetti F, Aiello LM, Quercia D. Personalized weight loss strategies by mining activity tracker data. User Modeling and User-Adapted Interaction 2020;30(3):447
    CrossRef
  5. Forman EM, Kerrigan SG, Butryn ML, Juarascio AS, Manasse SM, Ontañón S, Dallal DH, Crochiere RJ, Moskow D. Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?. Journal of Behavioral Medicine 2019;42(2):276
    CrossRef
  6. Stuber JM, Mackenbach JD, de Boer FE, de Bruijn G, Gillebaart M, Harbers MC, Hoenink JC, Klein MCA, Middel CNH, van der Schouw YT, Schuitmaker-Warnaar TJ, Velema E, Vos AL, Waterlander WE, Lakerveld J, Beulens JWJ. Reducing cardiometabolic risk in adults with a low socioeconomic position: protocol of the Supreme Nudge parallel cluster-randomised controlled supermarket trial. Nutrition Journal 2020;19(1)
    CrossRef
  7. Hagen L, Jiang Y, Knäuper B, Uetake K, Yang N. Mobile Health Behavior Tracking: Health Effects of Tracking Consistency and Its Prediction. SSRN Electronic Journal 2020;
    CrossRef
  8. Aguilera A, Figueroa CA, Hernandez-Ramos R, Sarkar U, Cemballi A, Gomez-Pathak L, Miramontes J, Yom-Tov E, Chakraborty B, Yan X, Xu J, Modiri A, Aggarwal J, Jay Williams J, Lyles CR. mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study. BMJ Open 2020;10(8):e034723
    CrossRef
  9. Zhou M, Fukuoka Y, Goldberg K, Vittinghoff E, Aswani A. Applying machine learning to predict future adherence to physical activity programs. BMC Medical Informatics and Decision Making 2019;19(1)
    CrossRef
  10. Ghelani DP, Moran LJ, Johnson C, Mousa A, Naderpoor N. Mobile Apps for Weight Management: A Review of the Latest Evidence to Inform Practice. Frontiers in Endocrinology 2020;11
    CrossRef
  11. Aswani A, Kaminsky P, Mintz Y, Flowers E, Fukuoka Y. Behavioral modeling in weight loss interventions. European Journal of Operational Research 2019;272(3):1058
    CrossRef
  12. Sporrel K, Nibbeling N, Wang S, Ettema D, Simons M. Unraveling mHealth exercise interventions for adults: A scoping review on the implementations and designs of persuasive strategies (Preprint). JMIR mHealth and uHealth 2019;
    CrossRef
  13. Hunter RF, Gough A, Murray JM, Tang J, Brennan SF, Chrzanowski-Smith OJ, Carlin A, Patterson C, Longo A, Hutchinson G, Prior L, Tully MA, French DP, Adams J, McIntosh E, Xin Y, Kee F. A loyalty scheme to encourage physical activity in office workers: a cluster RCT. Public Health Research 2019;7(15):1
    CrossRef
  14. Cox DJ. The Many Functions of Quantitative Modeling. Computational Brain & Behavior 2019;2(3-4):166
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.9117):

  1. John M, Kleppisch M. Prävention und Gesundheitsförderung. 2019. Chapter 108-1:1
    CrossRef