Enhancing clinical documentations through LLM

The project focuses on transforming clinical documentation with advanced AI, specifically Large Language Models (LLMs), to alleviate the burden on healthcare professionals. Aimed at improving efficiency and accuracy, the strategy involves creating an AI-powered charting assistant that seamlessly turns clinician-patient interactions into standardized clinical documents, offered as a subscription-based SaaS platform. Initiatives include fine-tuning LLMs with anonymized data, integrating with EHR systems, upholding stringent data security standards, engaging in rigorous testing with healthcare practitioners, and piloting with institutional partners. It incorporates NLP, machine learning, and agile development to continually refine the AI, benefiting particularly small, rural, and indigenous clinics, with the ultimate goal of enhancing clinical quality and patient care.

Faculty Supervisor:

Gregory Richards;Sukhjit Singh Sehra;Sonja Arias;Gregory Richards

Student:

Partner:

Empathia AI Canada, Inc.

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Ottawa; Wilfrid Laurier University

Program: