Machine Learning for Increasing the Speed and Quality of Service in Online Medical Services

Telehealth/Telemedicine covers a variety of medical services offered through media such as telephone, email and the internet. As technology evolves, these online medical services can be further enhanced to improve the user experience. In this project, we aim to focus on a particular set-up where the patients interact with doctors over a chat service. The chat service employs a number of doctors with varying specialties, and at any time during a doctor’s work hour, he/she might interact with up to five patients concurrently. Accordingly, it would be essential to improve the flow of information between doctors and the patients. We aim to employ natural language processing and machine learning based approaches to improve the user experience in chat services. Further, we plan to investigate time series prediction methods for predicting the volume of patients requesting chat services over a given period of time.

Faculty Supervisor:

Mucahit Cevik

Student:

Ozan Ozyegen;Hadi Jahanshahi

Partner:

Your Doctors Online

Discipline:

Engineering - mechanical

Sector:

Health care and social assistance

University:

Ryerson University