Cohort Builder: A Software Pipeline for Generating Patient Cohorts with Predetermined Baseline Characteristics from Medical Records and Raw Ophthalmic Imaging Data

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Version: Final published version
Licence: CC BY-NC 4.0
ID Serval
serval:BIB_A21A8D0481BB
Type
Partie de livre
Sous-type
Chapitre: chapitre ou section
Collection
Publications
Institution
Titre
Cohort Builder: A Software Pipeline for Generating Patient Cohorts with Predetermined Baseline Characteristics from Medical Records and Raw Ophthalmic Imaging Data
Titre du livre
Digital Health and Informatics Innovations for Sustainable Health Care Systems
Auteur⸱e⸱s
Mousavi Sepehr, Garjani Ali, Elwakil Adham, Brock Laurent Pierre, Dherse Alexandre, Forestier Edwige, Palaz Marine, Seiler Emilien, Duriez Alexia, Martin Thibaud, Wolfensberger Thomas, Schlingemann Reinier, Meloni Ilenia, Bergin Ciara, Tomasoni Mattia
Editeur
IOS Press
ISBN
9781643685335
ISSN
0926-9630
1879-8365
ISSN-L
0926-9630
Statut éditorial
Publié
Date de publication
22/08/2024
Peer-reviewed
Oui
Volume
316
Série
Studies in health technology and informatics
Pages
1151-1155
Langue
anglais
Résumé
In clinical research, the analysis of patient cohorts is a widely employed method for investigating relevant healthcare questions. The ability to automatically extract large-scale patient cohorts from hospital systems is vital in order to unlock the potential of real-world clinical data, and answer pivotal medical questions through retrospective research studies. However, existing medical data is often dispersed across various systems and databases, preventing a systematic approach to access and interoperability. Even when the data are readily accessible, clinical researchers need to sift through Electronic Medical Records, confirm ethical approval, verify status of patient consent, check the availability of imaging data, and filter the data based on disease-specific image biomarkers. We present Cohort Builder, a software pipeline designed to facilitate the creation of patient cohorts with predefined baseline characteristics from real-world ophthalmic imaging data and electronic medical records. The applicability of our approach extends beyond ophthalmology to other medical domains with similar requirements such as neurology, cardiology and orthopedics.
Pubmed
Open Access
Oui
Création de la notice
30/08/2024 9:45
Dernière modification de la notice
05/09/2024 9:10
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