Please note that all sessions are presented live at 12pm Eastern Time.

September 7 - Session 1

An Introduction to Artificial Intelligence and Machine Learning with Applications in Healthcare

In this session, Dr. Valafar will provide an introductory overview of the domain of Artificial Intelligence and Machine Learning. The session will include a brief overview of various techniques, an abstract view of training and testing AI models, some applications in the domain of Healthcare, and some of the challenges ahead.

September 14 - Session 2

Artificial Intelligence: Preparing for the Next Paradigm Shift in Medical Education

During this session participants will learn about the impact that artificial intelligence (AI) and machine learning (ML) will have on the practice of medicine, and subsequently medical education. Participants will learn what AI and ML are, and current applications in healthcare. Finally, participants will be able to identify opportunities for incorporating AI/ML content into their curricula.

September 21 - Session 3

Transforming Healthcare Together: Empowering Health Professionals to Address Bias in the Rapidly Evolving AI-Driven Landscape

As the interest in utilizing AI/machine learning in healthcare continues to grow, healthcare systems are adopting algorithms to enhance patient care, alleviate clinician burnout, and improve operational efficiency. However, while these applications may appear promising, they also carry certain risks, including the potential to automate and reinforce existing health disparities.

During this seminar, we will introduce the ABCDS Oversight framework developed at Duke Health. This comprehensive framework focuses on the governance, evaluation, and monitoring of clinical algorithms, providing participants with practical guidance to ensure the responsible implementation of AI/ML. Specifically, we will highlight how high-level principles can be translated into actionable steps for developers, allowing them to maximize patient benefit while minimizing potential risks.

Additionally, we will provide participants with our Bias Analysis and Mitigation template, a valuable tool for identifying and addressing potential sources of bias in AI/ML algorithms. This template facilitates the anticipation of associated harms and guides the implementation of strategies to mitigate or prevent biases. By utilizing this tool, developers can proactively address bias concerns and work towards equitable healthcare outcomes.

We will also address the challenges posed by large language models (LLMs) powered by generative AI, such as ChatGPT. While LLMs have the ability to generate text, their outputs must be carefully monitored and controlled to avoid unintended biases or misinformation. We will explore considerations and strategies necessary for effectively evaluating and governing LLMs within the healthcare context.

Lastly, we will discuss the competencies needed for educators working to prepare the next generation of health professionals. Universities can play a crucial role in supporting healthcare professionals to build critical competencies in AI/ML by strengthening curricula and providing opportunities for continuing professional development.

Whether you are a developer, a healthcare professional, or simply an enthusiast in the field of AI/ML, this seminar will offer valuable insights and practical tools for promoting responsible and equitable implementation of AI/ML in healthcare settings. Join us to learn how you can contribute to shaping the future of healthcare delivery through AI/ML innovation, educating next-generation health professionals, and ensuring the best possible outcomes for patients at Duke and beyond.

September 28 - Session 4

AI Tools for Medical Educators

Generative AI, including Large Language Models (LLMs) such as ChatGPT, has grown in skills and capacity in the past few months. Many of these news reports have focused on the impact of ChatGPT in an educational setting. Join us on September 28, when members of the USU faculty, the LRC, and the CIO teams discuss AI for Medical Educators as well as similar dialog-based tools. We will explain what they are, present considerations for the educational use of Generative AI, describe possible learning impacts, and discuss early policies and an ethical framework that relates to Generative AI. We will also discuss how ChatGPT works and provide you with some considerations for learning and assessment. This session will be presented by Dr. Clifton Dalgard, Dr. Joshua Duncan, Dr. Vincent Capaldi, Dr. Greg Booth, Dr. Elizabeth Steinbach, Ms. Alison Rollins, Dr. Seth Schobel Mr. Sean Baker, Dr. Dina Kurzweil & the Education & Technology Innovation (ETI) Support Office.

October 5 - Session 5

ChatGPT and Other AI Tools for Medicine and Medical Education

Webinar will cover:

1. Brief introduction of AI tools that medical students (health professions learners ) can use including ChatGPT.

2. Applying ChatGPT and other AI tools to learning in medical education/health professions education.

3. Academic misconduct and other risks of ChatGPT and AI tools

4. Future directions for ChatGPT and other AI tools