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The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data.

Publication ,  Journal Article
Bent, B; Wang, K; Grzesiak, E; Jiang, C; Qi, Y; Jiang, Y; Cho, P; Zingler, K; Ogbeide, FI; Zhao, A; Runge, R; Sim, I; Dunn, J
Published in: Journal of clinical and translational science
July 2020

Digital health is rapidly expanding due to surging healthcare costs, deteriorating health outcomes, and the growing prevalence and accessibility of mobile health (mHealth) and wearable technology. Data from Biometric Monitoring Technologies (BioMeTs), including mHealth and wearables, can be transformed into digital biomarkers that act as indicators of health outcomes and can be used to diagnose and monitor a number of chronic diseases and conditions. There are many challenges faced by digital biomarker development, including a lack of regulatory oversight, limited funding opportunities, general mistrust of sharing personal data, and a shortage of open-source data and code. Further, the process of transforming data into digital biomarkers is computationally expensive, and standards and validation methods in digital biomarker research are lacking.In order to provide a collaborative, standardized space for digital biomarker research and validation, we present the first comprehensive, open-source software platform for end-to-end digital biomarker development: The Digital Biomarker Discovery Pipeline (DBDP).Here, we detail the general DBDP framework as well as three robust modules within the DBDP that have been developed for specific digital biomarker discovery use cases.The clear need for such a platform will accelerate the DBDP's adoption as the industry standard for digital biomarker development and will support its role as the epicenter of digital biomarker collaboration and exploration.

Duke Scholars

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Published In

Journal of clinical and translational science

DOI

EISSN

2059-8661

ISSN

2059-8661

Publication Date

July 2020

Volume

5

Issue

1

Start / End Page

e19
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bent, B., Wang, K., Grzesiak, E., Jiang, C., Qi, Y., Jiang, Y., … Dunn, J. (2020). The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data. Journal of Clinical and Translational Science, 5(1), e19. https://doi.org/10.1017/cts.2020.511
Bent, Brinnae, Ke Wang, Emilia Grzesiak, Chentian Jiang, Yuankai Qi, Yihang Jiang, Peter Cho, et al. “The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data.Journal of Clinical and Translational Science 5, no. 1 (July 2020): e19. https://doi.org/10.1017/cts.2020.511.
Bent B, Wang K, Grzesiak E, Jiang C, Qi Y, Jiang Y, et al. The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data. Journal of clinical and translational science. 2020 Jul;5(1):e19.
Bent, Brinnae, et al. “The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data.Journal of Clinical and Translational Science, vol. 5, no. 1, July 2020, p. e19. Epmc, doi:10.1017/cts.2020.511.
Bent B, Wang K, Grzesiak E, Jiang C, Qi Y, Jiang Y, Cho P, Zingler K, Ogbeide FI, Zhao A, Runge R, Sim I, Dunn J. The digital biomarker discovery pipeline: An open-source software platform for the development of digital biomarkers using mHealth and wearables data. Journal of clinical and translational science. 2020 Jul;5(1):e19.
Journal cover image

Published In

Journal of clinical and translational science

DOI

EISSN

2059-8661

ISSN

2059-8661

Publication Date

July 2020

Volume

5

Issue

1

Start / End Page

e19