AI IN HEALTHCARE: A PRACTICAL INTRODUCTION

Prerequisites & course information

Requisites: MED SC-M 810 , 811 , 812 , and 813 Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Describe the core concepts of AI, including machine learning (ML), deep learning (DL), natural language processing (NLP), and multimodal AI. Audience: Graduate 2. Analyze the applications, potential, and impact of AI in various medical specialties, including radiology, pathology, cardiology, and surgery. Audience: Graduate 3. Evaluate the ethical and societal implications of AI in healthcare, such as bias, privacy, and the impact on the patient-physician relationship. Audience: Graduate 4. Appraise the strengths and limitations of AI algorithms in clinical decision-making. Audience: Graduate 5. Communicate effectively about AI with patients, colleagues, and the public. Audience: Graduate 6. Assess the public health implications of AI in healthcare, including access, equity, and community impact. Audience: Graduate 7. Analyze the impact of AI on population health and health disparities, and propose solutions to improve health equity. Audience: Graduate Learning Outcomes: 1. Describe the core concepts of AI, including machine learning (ML), deep learning (DL), natural language processing (NLP), and multimodal AI. Audience: Graduate 2. Analyze the applications, potential, and impact of AI in various medical specialties, including radiology, pathology, cardiology, and surgery. Audience: Graduate 3. Evaluate the ethical and societal implications of AI in healthcare, such as bias, privacy, and the impact on the patient-physician relationship. Audience: Graduate 4. Appraise the strengths and limitations of AI algorithms in clinical decision-making. Audience: Graduate 5. Communicate effectively about AI with patients, colleagues, and the public. Audience: Graduate 6. Assess the public health implications of AI in healthcare, including access, equity, and community impact. Audience: Graduate 7. Analyze the impact of AI on population health and health disparities, and propose solutions to improve health equity. Audience: Graduate