AI Ethics and Explainable AI (XAI) in Healthcare

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Course Overview

Home >Courses >AI Ethics and Explainable AI (XAI) in Healthcare

Mentor Based

Program Syllabus

Module 1

About This Course

This program emphasizes the ethical considerations of using AI in healthcare, such as fairness, bias, accountability, and patient privacy. Additionally, it covers Explainable AI (XAI) methodologies that ensure transparency, allowing healthcare professionals and patients to understand the decisions made by AI systems. The program integrates hands-on experience with case studies of AI implementations in healthcare, addressing ethical dilemmas and regulatory frameworks.

Module 2

Aim

To explore the intersection of AI ethics and Explainable AI (XAI) in the healthcare industry. This program is designed to equip PhD scholars, academicians, and healthcare professionals with knowledge of ethical challenges and explainability in AI-powered healthcare applications, ensuring trust, transparency, and fairness in medical AI systems.

Module 3

Program Objectives

Understand key ethical concerns in AI systems for healthcare.
Master techniques in Explainable AI (XAI) to ensure transparency in medical AI applications.
Explore real-world case studies of ethical AI in healthcare.
Learn about regulatory frameworks governing AI in healthcare.
Gain hands-on experience in building explainable AI models for healthcare.

Module 4

Program Structure

Lead Instructor

Dr. Sarah Chen

PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.

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