Real-World Diagnostic Accuracy of Fully Autonomous, FDA-Approved Artificial Intelligence Systems for Diabetic Retinopathy Screening in the United States: A Systematic Review and Meta-Analysis
- DOI
- 10.21203/rs.3.rs-10570689/v1
- Published
- 2026-08-04
- Container
- Not recorded
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 39/100 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.
- 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.
- cautionPublication version: Identified as a preprint; peer review and later versions may change the record.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.21203/rs.3.rs-10570689/v1,
title = {Real-World Diagnostic Accuracy of Fully Autonomous, FDA-Approved Artificial Intelligence Systems for Diabetic Retinopathy Screening in the United States: A Systematic Review and Meta-Analysis},
author = {Parimoo S.},
year = {2026},
doi = {10.21203/rs.3.rs-10570689/v1},
url = {https://doi.org/10.21203/rs.3.rs-10570689/v1}
}RIS
TY - JOUR TI - Real-World Diagnostic Accuracy of Fully Autonomous, FDA-Approved Artificial Intelligence Systems for Diabetic Retinopathy Screening in the United States: A Systematic Review and Meta-Analysis AU - Parimoo S. PY - 2026 DO - 10.21203/rs.3.rs-10570689/v1 UR - https://doi.org/10.21203/rs.3.rs-10570689/v1 ER -
APA
S., P. (2026). Real-World Diagnostic Accuracy of Fully Autonomous, FDA-Approved Artificial Intelligence Systems for Diabetic Retinopathy Screening in the United States: A Systematic Review and Meta-Analysis. https://doi.org/10.21203/rs.3.rs-10570689/v1
Source records
- europe-pmc · retrieved 2026-09-26T14:37:32.561Z