Mastering ATLAS Cohort Definitions: A Clinical Researcher's Complete Guide
Learn how to build reproducible patient cohorts in OHDSI ATLAS with a hands-on Type 2 Diabetes use case, backend table explanations, and lessons learned.
Exploring clinical informatics, healthcare AI, and the OHDSI ecosystem. Deep dives into OMOP CDM, NLP pipelines, and real-world evidence generation.
Learn how to build reproducible patient cohorts in OHDSI ATLAS with a hands-on Type 2 Diabetes use case, backend table explanations, and lessons learned.
Understanding the standardized vocabularies that power the OMOP Common Data Model. How to navigate concept hierarchies and build effective concept sets.
Building a complete ETL pipeline to transform Synthea synthetic patient data into OMOP CDM format using Python and PostgreSQL.
Running Achilles to characterize your OMOP database, understanding the results tables, and identifying data quality issues before analysis.
From raw clinical notes to structured OMOP data. Implementing named entity recognition, concept normalization, and relation extraction.
Step-by-step guide to deploying the complete OHDSI stack with Docker Compose. ATLAS, WebAPI, and connecting external databases.
The definitive guide to observational health data science. Free online at ohdsi.github.io/TheBookOfOhdsi.
Free online courses for OHDSI tools and OMOP CDM. Start learning at academy.ehden.eu.