Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges
- DOI
- 10.1148/ryai.230227
- Published
- 2024-05-01
- Container
- Radiology: Artificial Intelligence
- Publisher
- Radiological Society of North America (RSNA)
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1148/ryai.230227,
title = {Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges},
author = {Felipe C. Kitamura and Luciano M. Prevedello and Errol Colak and Safwan S. Halabi and Matthew P. Lungren and Robyn L. Ball and Jayashree Kalpathy-Cramer and Charles E. Kahn and Tyler Richards and Jason F. Talbott and George Shih and Hui Ming Lin and Katherine P. Andriole and Maryam Vazirabad and Bradley J. Erickson and Adam E. Flanders and John Mongan},
year = {2024},
journal = {Radiology: Artificial Intelligence},
doi = {10.1148/ryai.230227},
url = {https://doi.org/10.1148/ryai.230227}
}RIS
TY - JOUR TI - Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges AU - Felipe C. Kitamura AU - Luciano M. Prevedello AU - Errol Colak AU - Safwan S. Halabi AU - Matthew P. Lungren AU - Robyn L. Ball AU - Jayashree Kalpathy-Cramer AU - Charles E. Kahn AU - Tyler Richards AU - Jason F. Talbott AU - George Shih AU - Hui Ming Lin AU - Katherine P. Andriole AU - Maryam Vazirabad AU - Bradley J. Erickson AU - Adam E. Flanders AU - John Mongan PY - 2024 JO - Radiology: Artificial Intelligence DO - 10.1148/ryai.230227 UR - https://doi.org/10.1148/ryai.230227 ER -
APA
Kitamura, F. C., Prevedello, L. M., Colak, E., Halabi, S. S., Lungren, M. P., Ball, R. L., Kalpathy-Cramer, J., Kahn, C. E., Richards, T., Talbott, J. F., Shih, G., Lin, H. M., Andriole, K. P., Vazirabad, M., Erickson, B. J., Flanders, A. E., & Mongan, J. (2024). Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiology: Artificial Intelligence. https://doi.org/10.1148/ryai.230227
Source records
- crossref · retrieved 2026-11-05T08:43:18.616Z