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

Formative Evaluation of Digital Health Interventions (2226) mHealth for Data Collection and Research (917) User-centred Design Case Studies (564) Participatory Design and Participatory Research (305) Cardiovascular Disease Prevention (115) Formative Studies and eHealth/mHealth Development (516)

Published on in Vol 6, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25444, first published .
An Open-Source Privacy-Preserving Large-Scale Mobile Framework for Cardiovascular Health Monitoring and Intervention Planning With an Urban African American Population of Young Adults: User-Centered Design Approach

An Open-Source Privacy-Preserving Large-Scale Mobile Framework for Cardiovascular Health Monitoring and Intervention Planning With an Urban African American Population of Young Adults: User-Centered Design Approach

An Open-Source Privacy-Preserving Large-Scale Mobile Framework for Cardiovascular Health Monitoring and Intervention Planning With an Urban African American Population of Young Adults: User-Centered Design Approach

Authors of this article:

Gari Clifford1, 2 Author Orcid Image ;   Tony Nguyen1 Author Orcid Image ;   Corey Shaw1 Author Orcid Image ;   Brittney Newton3 Author Orcid Image ;   Sherilyn Francis3, 4 Author Orcid Image ;   Mohsen Salari1 Author Orcid Image ;   Chad Evans5 Author Orcid Image ;   Camara Jones5 Author Orcid Image ;   Tabia Henry Akintobi6 Author Orcid Image ;   Herman Taylor Jr5 Author Orcid Image
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Journals

  1. Cuevas-Chávez A, Hernández Y, Ortiz-Hernandez J, Sánchez-Jiménez E, Ochoa-Ruiz G, Pérez J, González-Serna G. A Systematic Review of Machine Learning and IoT Applied to the Prediction and Monitoring of Cardiovascular Diseases. Healthcare 2023;11(16):2240 View