In today's fast-paced health services environment, knowing how to use data and AI is crucial for driving impactful research and improving patient outcomes. However, many professionals lack the skills and knowledge to effectively integrate AI into their work, missing out on opportunities to innovate and elevate their research practices.
Registration is now closed. Please complete this form to receive updates, and announcements regarding future offerings for this course.
Are you ready to revolutionize your approach to health care delivery, research, and population health through data science and AI? "Leveraging AI for High-Impact Health Research," a new online course in collaboration with WashU Medicine Institute for Informatics, Data Science and Biostatistics (I2DB), is designed to help professionals transform their approach to health care delivery, research, and population health through data science and AI. Through real-world scenarios, toolkits, and live sessions with leading AI and academic experts, participants will master AI literacy and practical skills to design, implement and evaluate AI interventions in health research.
This course will teach you how to:
Module 1: Foundations of AI in Health Research
Explore the history, evolution, and impact of AI in health care–particularly in medical imaging and electronic health records. Learn key concepts to guide effective selection and use of AI tools–and to understand how these integrate into the data science lifecycle.
Module 2: Data Use and Engineering
Learn how to extract valuable insights from diverse health care data sources, and how to identify those data sources best suited for various AI applications. This module covers the hierarchy of data types, data manipulation techniques, and the challenges of working with both structured and unstructured data to improve AI models.
Module 3: Best Practices in AI Implementation
Gain practical knowledge on selecting and applying strategies for implementing AI in health research. Learn best practices for AI development, evaluation, and governance, with a focus on prompt engineering and real-world applications. Understand the emerging standards and challenges in AI reporting.
Module 4: AI for Phenotyping
Understand and apply AI tools for extracting information from clinical records, by learning about advancements in using them for extracting concepts from clinical notes, generating queries for clinical databases, and evaluating their capabilities. This module focuses on the direct application of AI to clinical data, and students will learn both how AI is applied as well as how to develop a strategy for using AI effectively.
| Member | Non-Member |
| $999 | $1350 |
Group Discount
Save $100 per person when you register a group of three or more for the Leveraging AI for High-Impact Health Research course. This discount is available through Thursday, March 27. To take advantage of this offer, email registrations@academyhealth.org before completing your online registration process to receive a promo code and save on enrollment costs.
Receipts & Confirmations
Detailed receipts can be found in “My Orders” via your AcademyHealth account, or available upon request. If you would like one, please send a request to registrations@academyhealth.org. Payment receipts will be sent to the email address provided on the registration form.
Cancellations
All cancellations must be received in writing or via email by Tuesday, March 5, 2025. Registration fees for cancelled registrants may not be applied to future AcademyHealth meetings.
Dr. Wilcox is a Professor of Medicine and the Director of the Center for Applied Clinical Informatics, Institute for Informatics, Washington University in St. Louis School of Medicine. Read Bio
Dr. Aditi Gupta, is an Assistant Professor in the Washington University Institute for Informatics and the Division of Biostatistics. Read Bio
Dr. Payne is an internationally recognized leader in the field of clinical research informatics (CRI) and translational bioinformatics (TBI). His research portfolio is actively supported by a combination of NCATS, NLM, and NCI grants and contracts, as well as a variety of awards from both nonprofit and philanthropic organizations. Read Bio
Ms. Borlawsky-Payne is a lecturer in the WashU Institute for Informatics, Data Science & Biostatistics. Read Bio