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

Engagement with and Adherence to Digital Health Interventions, Law of Attrition (491) Innovations and Technology for Healthy Eating Education (414) Innovations and Technology for Physical Activity Education (742) mHealth for Wellness, Behavior Change and Prevention (2871)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22184, first published .
Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study

Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study

Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study

Authors of this article:

Hongwook Kwon1 Author Orcid Image ;   Ho Heon Kim1 Author Orcid Image ;   Jaeil An1 Author Orcid Image ;   Jae-Ho Lee2, 3 Author Orcid Image ;   Yu Rang Park1 Author Orcid Image
Article Authors Cited by (10) Tweetations (5) Metrics

Journals

  1. Labonté K, Knäuper B, Dubé L, Yang N, Nielsen D. Adherence to a caloric budget and body weight change vary by season, gender, and BMI: An observational study of daily users of a mobile health app. Obesity Science & Practice 2022;8(6):735 View
  2. Kim S, Lee H. Customer Churn Prediction in Influencer Commerce: An Application of Decision Trees. Procedia Computer Science 2022;199:1332 View
  3. Tamblyn R, Brieva J, Cain M, Martinez F. The Effects of Introducing a Mobile App–Based Procedural Logbook on Trainee Compliance to a Central Venous Catheter Insertion Accreditation Program: Before-and-After Study. JMIR Human Factors 2022;9(1):e35199 View
  4. Vergnolle G, Lahrichi N. Data-Driven Analysis of Employee Churn in the Home Care Industry. Home Health Care Management & Practice 2023;35(2):75 View
  5. Ahn D, Lee D, Hosanagar K. Modeling Lengthy Behavioral Log Data for Customer Churn Management: A Representation Learning Approach. SSRN Electronic Journal 2021 View
  6. Lee Y, Jang Y, Lee S. Obstacles to Health Big Data Utilization Based on the Perceptions and Demands of Health Care Workers in South Korea: Web-Based Survey Study. JMIR Formative Research 2023;7:e45913 View
  7. Gani Joy U, Hoque K, Nazim Uddin M, Chowdhury L, Park S. A Big Data-Driven Hybrid Model for Enhancing Streaming Service Customer Retention Through Churn Prediction Integrated With Explainable AI. IEEE Access 2024;12:69130 View
  8. Baee S, Eberle J, Baglione A, Spears T, Lewis E, Behan H, Wang H, Funk D, Teachman B, E Barnes L. Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: Machine Learning Study (Preprint). JMIR Mental Health 2023 View

Books/Policy Documents

  1. Zhao Z, Zhou W, Qiu Z, Li A, Wang J. Business Intelligence and Information Technology. View