Cited by 34Mobile Health and mHealth ApplicationsArtificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Author Correction: Developing and adopting safe and effective digital biomarkers to improve patient outcomes

Open access
Coravos, Andrea, Khozin, Sean, Mandl, Kenneth D.·2019·npj Digital Medicine

Abstract

The original version of the published Article mistakenly omitted the second affiliation for the first Author, Andrea Coravos. The first Author’s affiliation has been updated to include Harvard-MIT Center for Regulatory Science, Boston, MA, USA. This has been corrected in the HTML and PDF version of the Article.

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Crossref · 10.1038/s41746-019-0119-8

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Authors
Coravos, A., Khozin, S., & Mandl, K. D.
Affiliations
  • Boston Children's Hospital (US)
  • United States Food and Drug Administration (US)
Corresponding author
Mandl, Kenneth D.
Venue
npj Digital Medicine
Published
2019-05-10
Volume
2
Issue
1
Pages
40-40
ISSN
2398-6352 (ISSN-L)
OpenAlex
W2944492170
Cited by
34
References
0
Citations by year
2026: 3 · 2025: 6 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 12 · 2020: 5 · 2019: 1
Type
journal article
Language
en
Open access
Locations
  • npj Digital Medicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords
digital biomarkers, patient outcomes, regulatory science

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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