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

Machine Learning (1971) Decision Support for Health Professionals (1468) Electronic Health Records (1271)

Published on in Vol 10, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31480, first published .
A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study

A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study

A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study

Authors of this article:

Tjeerd van der Ploeg1 Author Orcid Image ;   Robbert Gobbens1, 2, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. van der Ploeg T, Gobbens R, Salem B. Bayesian Techniques in Predicting Frailty among Community-Dwelling Older Adults in the Netherlands. Archives of Gerontology and Geriatrics 2023;105:104836 View
  2. van der Ploeg T, Schalk R, Gobbens R. External Validation of Models for Predicting Disability in Community-Dwelling Older People in the Netherlands: A Comparative Study. Clinical Interventions in Aging 2023;Volume 18:1873 View
  3. van der Ploeg T, Gobbens R. The Prediction of Healthcare Utilization by Frailty and Disability among Dutch Community-Dwelling People Aged 75 Years or Older. The Journal of Frailty & Aging 2024;13(4):474 View
  4. Kang B, Park M, Kim J, Yoon S, Heo S, Kang C, Lee S, Choi Y, Hong D. Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach. Journal of Medical Internet Research 2025;27:e69379 View