This paper is in the following e-collection/theme issue:

Machine Learning (1121) Clinical Information and Decision Making (1042) Electronic Health Records (839) Innovations and Technology in Cancer Care (330) Decision Support for Health Professionals (854) Secondary Use of Clinical Data for Research and Surveillance (266) Precision Medicine (43) Precision Medicine and Genetics (37)

Published on in Vol 9 , No 5 (2021) :May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23586, first published .
Leveraging Genetic Reports and Electronic Health Records for the Prediction of Primary Cancers: Algorithm Development and Validation Study

Leveraging Genetic Reports and Electronic Health Records for the Prediction of Primary Cancers: Algorithm Development and Validation Study

Leveraging Genetic Reports and Electronic Health Records for the Prediction of Primary Cancers: Algorithm Development and Validation Study

Authors of this article:

Nansu Zong 1 Author Orcid Image ;   Victoria Ngo 2 Author Orcid Image ;   Daniel J Stone 1 Author Orcid Image ;   Andrew Wen 1 Author Orcid Image ;   Yiqing Zhao 1 Author Orcid Image ;   Yue Yu 1 Author Orcid Image ;   Sijia Liu 1 Author Orcid Image ;   Ming Huang 1 Author Orcid Image ;   Chen Wang 1 Author Orcid Image ;   Guoqian Jiang 1 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Prud'hommeaux E, Collins J, Booth D, Peterson K, Solbrig H, Jiang G. Development of a FHIR RDF data transformation and validation framework and its evaluation. Journal of Biomedical Informatics 2021;117:103755 View
  2. González-Castro L, Cal-González V, Del Fiol G, López-Nores M. CASIDE: A data model for interoperable cancer survivorship information based on FHIR. Journal of Biomedical Informatics 2021;124:103953 View
  3. Duda S, Kennedy N, Conway D, Cheng A, Nguyen V, Zayas-Cabán T, Harris P. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review. Journal of the American Medical Informatics Association 2022;29(9):1642 View
  4. Xiao G, Pfaff E, Prud'hommeaux E, Booth D, Sharma D, Huo N, Yu Y, Zong N, Ruddy K, Chute C, Jiang G. FHIR-Ontop-OMOP: Building clinical knowledge graphs in FHIR RDF with the OMOP Common data Model. Journal of Biomedical Informatics 2022;134:104201 View
  5. He T, Belouali A, Patricoski J, Lehmann H, Ball R, Anagnostou V, Kreimeyer K, Botsis T. Trends and opportunities in computable clinical phenotyping: A scoping review. Journal of Biomedical Informatics 2023;140:104335 View