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

Secondary Use of Clinical Data for Research and Surveillance (366) Clinical Informatics (1022) Electronic Health Records (1053) New Methods (944) Tools, Programs and Algorithms (266)

Published on in Vol 10, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38936, first published .
Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study

Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study

Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study

Authors of this article:

Antoine Lamer1, 2, 3 Author Orcid Image ;   Mathilde Fruchart1 Author Orcid Image ;   Nicolas Paris3 Author Orcid Image ;   Benjamin Popoff4 Author Orcid Image ;   Anaïs Payen1 Author Orcid Image ;   Thibaut Balcaen5 Author Orcid Image ;   William Gacquer6 Author Orcid Image ;   Guillaume Bouzillé7 Author Orcid Image ;   Marc Cuggia7 Author Orcid Image ;   Matthieu Doutreligne8, 9 Author Orcid Image ;   Emmanuel Chazard1 Author Orcid Image
Article Authors Cited by (3) Tweetations (9) Metrics

Journals

  1. Lamer A, Saint-Dizier C, Paris N, Chazard E. Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline. JMIR Medical Informatics 2024;12:e54590 View
  2. Lamer A, Popoff B, Delange B, Doutreligne M, Chazard E, Marcilly R, Priou S, Quindroit P. Barriers encountered with clinical data warehouses: Recommendations from a focus group. Computer Methods and Programs in Biomedicine 2024;256:108404 View