Share Description
In this course, you will :
- Follow the patient's journey through the lens of the data generated at each encounter, leading us to a unique de-identified dataset created specifically for this specialisation.
- The data set includes both EHR and image data, and we will use it to build models that will allow us to make risk-stratification decisions for our patients.
- We'll go over how the various decisions you make, such as feature construction, data types to use, how the model evaluation is set up, and how you handle the patient timeline, affect the care that the model recommends.
- Throughout this exploration, we will also discuss the regulatory and ethical issues that arise as we attempt to use AI to assist us in making better care decisions for our patients. This course will provide students with hands-on experience in a medical data miner's day.
Syllabus :
- Data Collection
- Model Training
- Model Evaluation
- Model Deployment and Regulation, Wrap Up
