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

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 2022:108482232211373 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

Books/Policy Documents

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