04-801-T4   Project in AI for Healthcare

Course description

This is a practical course where students who have taken the companion 04-800-T3 mini-course, or who come with at least some artificial intelligence (AI) or machine learning (ML) background, tackle the challenges of working with real data to improve healthcare, particularly in Africa. While ML is applicable to a wide variety of problems in the different biosciences, this course focuses on the use of clinical data. Clinical topics that students may focus on will include risk classification, modeling of disease progression, customized diagnosis and medication; subtype discovery; clinical workflow improvement. Mathematical topics that students may focus on include graphical models, time-series analysis, deep learning and transfer learning, causality, interpretability, and algorithmic fairness. Students will be assessed on structured assignments integrated into a final project.

Learning objectives

The main objectives of this course are to:

• Apply relevant AI and MLalgorithms to solve problems in specific use cases in healthcare
• Define the scope and develop a detailed plan for executing a feasible healthcare project
• Account for practical considerations such as electronic tools, the integrity of data sources, data governance, and regulatory compliance
• Address the issue of fundamental value creation

Outcomes

Upon successful completion of this course, students should be able to:

• Engage in the usage and/or implementation of AI for healthcare in their institution
• Help develop new products for or improve the performance of a healthcare concern
• Effectively communicate technical recommendations

Content details

• Healthcare case selection and AI project proposal
• Simulation or implementation of a prototype
• Exercise in verification and validation against specified criteria
• Presentation of AI project plan and defense thereof

Prerequisites

04-801-T3 Applications of AI in Healthcare or by permission of the instructor.

Faculty

Ahmed Biyabani