Optimizing Pretrained Clinical Embeddings for Automatic COVID-related ICD Coding (Phase II)

We are building a machine-learning algorithm to be able to understand the unstructured clinical notes better and to identify the most appropriate ICD codes for each visit. This algorithm will help healthcare systems standardize and extract insights from these notes to make them more useful for determining how sick patients are, what procedures are performed and how patients are improving over time.

Faculty Supervisor:

Helen Chen

Student:

Georgios Michalopoulos

Partner:

Semantic Health Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

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