Automatically pre-screening patients for the rare disease aromatic <scp>l</scp>-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population
- DOI
- 10.1093/jamia/ocad244
- Published
- 2023-12-22
- Container
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- 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:10.1093/jamia/ocad244,
title = {Automatically pre-screening patients for the rare disease aromatic <scp>l</scp>-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population},
author = {Aaron M Cohen and Jolie Kaner and Ryan Miller and Jeffrey W Kopesky and William Hersh},
year = {2023},
journal = {Journal of the American Medical Informatics Association},
doi = {10.1093/jamia/ocad244},
url = {https://doi.org/10.1093/jamia/ocad244}
}RIS
TY - JOUR TI - Automatically pre-screening patients for the rare disease aromatic <scp>l</scp>-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population AU - Aaron M Cohen AU - Jolie Kaner AU - Ryan Miller AU - Jeffrey W Kopesky AU - William Hersh PY - 2023 JO - Journal of the American Medical Informatics Association DO - 10.1093/jamia/ocad244 UR - https://doi.org/10.1093/jamia/ocad244 ER -
APA
Cohen, A. M., Kaner, J., Miller, R., Kopesky, J. W., & Hersh, W. (2023). Automatically pre-screening patients for the rare disease aromatic <scp>l</scp>-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocad244
Source records
- crossref · retrieved 2026-09-25T09:02:56.882Z