Shawn Xiong, PhD: No financial relationships to disclose
This session will allow attendees to hear from individuals who plan to engage in AI with a focus on machine learning across a variety of settings. Machine learning (ML) approaches have been developed and applied to various areas in healthcare including diagnosis, treatment protocol development, drug development, personalized medicine, and patient care. This session will review how AI/ML is being leveraged in research to guide pharmaceutical outcomes research, policy, and practice in the future.
Learning Objectives:
Define AI and machine learning.
Identify best practices and science areas that are particularly useful for AI and machine learning.
Describe commonly used approaches for machine learning in practicing practice-based pharmacy research and pharmaceutical health services research.
Discuss natural language processing limitations in pharmaceutical practice and science and potential solutions.