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

New Methods (944) Machine Learning (1465) Preventing Social Isolation and Fostering Social Interactions in Old Age (64)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22339, first published .
Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study

Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study

Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study

Authors of this article:

Timothée Aubourg1, 2, 3 Author Orcid Image ;   Jacques Demongeot2, 3, 4 Author Orcid Image ;   Nicolas Vuillerme2, 3, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations (5) Metrics

Journals

  1. Ren B, Xia C, Gehrman P, Barnett I, Satterthwaite T. Measuring Daily Activity Rhythms in Young Adults at Risk of Affective Instability Using Passively Collected Smartphone Data: Observational Study. JMIR Formative Research 2022;6(9):e33890 View
  2. Breitinger S, Gardea-Resendez M, Langholm C, Xiong A, Laivell J, Stoppel C, Harper L, Volety R, Walker A, D'Mello R, Byun A, Zandi P, Goes F, Frye M, Torous J. Digital Phenotyping for Mood Disorders: Methodology-Oriented Pilot Feasibility Study. Journal of Medical Internet Research 2023;25:e47006 View