Synthetic data as an enabler for machine learning applications in medicine.
- DOI
- 10.1016/j.isci.2022.105331
- Published
- 2022-10-13
- Container
- iScience
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- supportingOpen access status: Normalized open-access status: open.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.isci.2022.105331,
title = {Synthetic data as an enabler for machine learning applications in medicine.},
author = {Rajotte JF and Bergen R and Buckeridge DL and El Emam K and Ng R and Strome E.},
year = {2022},
journal = {iScience},
doi = {10.1016/j.isci.2022.105331},
url = {https://doi.org/10.1016/j.isci.2022.105331}
}RIS
TY - JOUR TI - Synthetic data as an enabler for machine learning applications in medicine. AU - Rajotte JF AU - Bergen R AU - Buckeridge DL AU - El Emam K AU - Ng R AU - Strome E. PY - 2022 JO - iScience DO - 10.1016/j.isci.2022.105331 UR - https://doi.org/10.1016/j.isci.2022.105331 ER -
APA
JF, R., R, B., DL, B., K, E. E., R, N., & E., S. (2022). Synthetic data as an enabler for machine learning applications in medicine.. iScience. https://doi.org/10.1016/j.isci.2022.105331
Source records
- europe-pmc · retrieved 2026-09-27T07:47:42.679Z