OMOP CDM
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What is OMOP CDM?
The OMOP Common Data Model (CDM) is a data standard developed by the Observational Health Data Sciences and Informatics (OHDSI) collaborative. It transforms data from disparate sources into a common format and representation, facilitating standardized analyses and reproducible research across multiple healthcare databases. It is commonly used for observational research, such as studying drug safety, disease patterns, and treatment effectiveness.
What other technologies are related to OMOP CDM?
OMOP CDM Complementary Technologies
R
R is a statistical computing language often used for data analysis and visualization on OMOP CDM data, especially for cohort analysis and characterization.
Python
Python, with libraries like Pandas and NumPy, is used for data manipulation, analysis, and machine learning on OMOP CDM data. Also tools like OHDSI's 'Achilles' is Python code.
SQL
SQL is essential for querying and manipulating data within the OMOP CDM database. Almost all operations related to the OMOP CDM, whether data extraction, transformation, or loading, require SQL.
Number of organizations that mention technology
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Which job functions commonly mention OMOP CDM?
Bioinformatics
0.1% of all Bioinformatics jobs mention OMOP CDM
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jobs on Sumble
Data Engineer
21 Data Engineer jobs mention OMOP CDM
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jobs on Sumble
Data Scientist
15 Data Scientist jobs mention OMOP CDM
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jobs on Sumble
Scientist
11 Scientist jobs mention OMOP CDM
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jobs on Sumble
Data, Analytics & Machine Learning
31 Data, Analytics & Machine Learning jobs mention OMOP CDM
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jobs on Sumble
Which organizations are mentioning OMOP CDM?
Tufts Medical Center
Health Care and Social Assistance
Odysseus Data Services, Inc.
Professional Services
UC Irvine Health
Health Care and Social Assistance
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