Data mining of Clinical Databases – CDSS 1
Learn about MIMIC-III, the largest publicly available EHR database for benchmarking machine learning algorithms. Discover tools for querying, extracting, and visualizing descriptive analytics. Understand the schema and coding to map research questions and extract clinical outcomes for developing useful ML algorithms.
This course will introduce MIMIC-III, which is the largest publicly Electronic Health Record (EHR) database available to benchmark machine learning algorithms. In particular, you will learn about the design of this relational database, what tools are available to query, extract and visualise descriptive analytics.
The schema and International Classification of Diseases coding is important to understand how to map research questions to data and how to extract key clinical outcomes in order to develop clinically useful machine learning algorithms.
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