Solving medicine's data bottleneck: Nightingale Open Science
Open accessAbstract
Open datasets, curated around unsolved medical problems, are vital to the development of computational research in medicine, but remain in short supply. Nightingale Open Science, a non-profit computing platform, was founded to catalyse research in this nascent field.
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Deidentification and public release of data, often through consortium models, is an option for data sharing; CAMELYON and BraTS challenges have made large-scale deidentified datasets available, and the Nightingale Open Science Initiative aims to release more.
“The second option is deidentification and public release of data, usually via a consortium model.”
From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [165]
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- Authors
- Mullainathan, S., & Obermeyer, Z.
- Affiliations
- University of Chicago (US)
- University of California, Berkeley (US)
- Corresponding author
- Obermeyer, Ziad
- Venue
- Nature Medicine
- Published
- 2022-05
- Volume
- 28
- Issue
- 5
- Pages
- 897-899
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4229447538
- Cited by
- 43
- References
- 16
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 12 · 2023: 11
- FWCI
- 8.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Medicine (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Funders
- Gordon and Betty Moore Foundation
- National Institute on Aging (P01AG005842)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Social Sciences › Decision Sciences › Information Systems and Management › Interdisciplinary Research and Collaboration
- Keywords
- health data, computational medicine, data sharing, research infrastructure
- MeSH terms
- Medicine, Science
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