Automated clinical note generation from clinician-patient dialogues

This project will investigate improvements to models for automatically generating physician notes from transcripts of conversations between physicians and patients. The model will capture important medical information such as symptoms, treatments, and medications, and automatically formulate a free-text note that mimics the style of the physician’s manually entered notes. The model will use context and time information to ensure that the documentation is accurate and complete. This will allow physicians to spend more time focused on their patients, and less time documenting during and after the patient visit. This project will benefit the partner organization by improving the accuracy of the existing software pipeline.

Serena Jeblee
Faculty Supervisor: 
Frank Rudzicz;Yang Xu;Marsha Chechik
Partner University: