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Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54993, first published .
AIDAR health device and app showing daily health score of 70

Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational Study

Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational Study

Journals

  1. Pagliaro J, Wash L, Ly K, Mathew J, Leibowitz A, Cabrera R, Wormwood J, Vimalananda V. Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study. JMIR Formative Research 2025;9:e68676 View
  2. Peng B, Allen-Benson D, Talebi Y, Ghosh S, Yaseen A, Valerio-Shewmaker M, Boerwinkle E, DeSantis S, Swartz M, Cazaban C, Bi K. Temporal, Demographic, and Geographic Patterns of Long COVID Incidence in Relation to SARS-CoV-2 Variant Emergence: Insights from the Texas All-Payer Claims Database (TX-APCD). International Journal of Infectious Diseases 2026:109051 View