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Original Papers (2) New Methods (899) mHealth for Data Collection and Research (904) Digital Biomarkers and Digital Phenotyping (177) Machine Learning (1366) Artificial Intelligence (1181) Tools, Programs and Algorithms (236) Big Data (215) Development and Evaluation of Research Methods, Instruments and Tools (420) Advanced Data Analytics in eHealth (103)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47805, first published .
Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling

Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling

Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling

Authors of this article:

Tahsin Mullick1 Author Orcid Image ;   Sam Shaaban2 Author Orcid Image ;   Ana Radovic3 Author Orcid Image ;   Afsaneh Doryab1 Author Orcid Image
Article Authors Cited by Tweetations (4) Metrics

Tahsin Mullick   1 , MEng ;   Sam Shaaban   2 , MBA ;   Ana Radovic   3 , MD, MSc ;   Afsaneh Doryab   1 , PhD

1 Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, United States

2 NuRelm, Pittsburgh, PA, United States

3 Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, United States

Corresponding Author:

  • Tahsin Mullick, MEng
  • Department of Systems and Information Engineering
  • University of Virginia
  • Olsson Hall, 151 Engineer's Way
  • Charlottesville, VA, 22903
  • United States
  • Phone: 1 4349245393
  • Email: tum7q@virginia.edu