Optimizing Pretrained Clinical Embeddings for Automatic COVID-related ICD Coding

We are building a machine learning algorithm to be able to better understand the unstructured clinical notes that doctors write about patients. This will help hospitals and healthcare systems standardize and extract insights from these notes to make them more useful for determining how sick COVID patients are and how they 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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