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.
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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 partnership with Washington University in St. Louis, 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 Funding Mechanisms
Navigate the complexities of securing funding for AI projects in health care, by learning about different funding sources or mechanisms– as well as maturity models to assess project readiness, and key ethical considerations. Gain insights on how to secure funding for your AI-related projects by aligning your initiatives with funder priorities, processes, and requirements.
| Member | Non-Member |
| $999 | $1350 |
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 Monday, August 26, 2024. 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