Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.
- DOI
- 10.1002/pds.5648
- Published
- 2023 Oct
- Container
- Pharmacoepidemiology and drug safety
- 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:10.1002/pds.5648,
title = {Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.},
author = {Torgersen J and Akers S and Huo Y and Terry JG and Carr JJ and Ruutiainen AT and Skanderson M and Levin W and Lim JK and Taddei TH and So-Armah K and Bhattacharya D and Rentsch CT and Shen L and Carr R and Shinohara RT and McClain M and Freiberg M and Justice AC and Lo Re V 3rd},
year = {2023},
journal = {Pharmacoepidemiology and drug safety},
doi = {10.1002/pds.5648},
url = {https://doi.org/10.1002/pds.5648}
}RIS
TY - JOUR TI - Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV. AU - Torgersen J AU - Akers S AU - Huo Y AU - Terry JG AU - Carr JJ AU - Ruutiainen AT AU - Skanderson M AU - Levin W AU - Lim JK AU - Taddei TH AU - So-Armah K AU - Bhattacharya D AU - Rentsch CT AU - Shen L AU - Carr R AU - Shinohara RT AU - McClain M AU - Freiberg M AU - Justice AC AU - Lo Re V 3rd PY - 2023 JO - Pharmacoepidemiology and drug safety DO - 10.1002/pds.5648 UR - https://doi.org/10.1002/pds.5648 ER -
APA
J, T., S, A., Y, H., JG, T., JJ, C., AT, R., M, S., W, L., JK, L., TH, T., K, S., D, B., CT, R., L, S., R, C., RT, S., M, M., M, F., AC, J., & 3rd, L. R. V. (2023). Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.. Pharmacoepidemiology and drug safety. https://doi.org/10.1002/pds.5648
Source records
- pubmed · retrieved 2026-09-26T19:32:16.411Z