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

Sepehr Mousavi, Ali Garjani, Adham Elwakil, Laurent Pierre Brock, Alexandre Pierre Dherse,Edwige Forestier, Marine Palaz, Emilien Seiler, Alexia Duriez, Thibaud Martin, Thomas Wolfensburger,Reinier Schlingemann, Ilenia Meloni,Mattia Tomasoni

crossref(2024)

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摘要
Abstract In clinical research, the analysis of patient cohorts is a widely employed method for investigating relevant questions in healthcare. Furthermore, the availability of large-scale datasets opens the way for the integration of AI models into clinical practices. The ability to extract appropriate patient cohorts and large-scale datasets from hospital databases is vital in order to unlock the potential of real-world data collected in clinics and answer pivotal medical questions through retrospective studies. However, existing medical data is often dispersed across various systems and databases, preventing a systematic approach allowing access and interoperability. Even when the data are readily accessible, researchers need to systematically combine them to form study-specific cohorts with predefined baseline characteristics, tailored to answer specific research inquiries. This process is costly, repetitive, and error-prone, as it requires sifting through Electronic Medical Records, confirming ethical approval, verifying status of patient consent, checking the availability of imaging data, and filtering based on disease-specific image biomarkers. Our objective is to give the ability to craft study-specific patient cohorts to clinical researchers through an automated data preparation and processing pipeline. 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 orthopaedics.
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