Join HealthAdvocateX for a discussion of artificial intelligence (AI)/machine learning (ML) in healthcare. First, we will discuss the nuances of Bias and Fairness in AI/ML Healthcare Applications, exploring how these technologies impact healthcare outcomes. Then, we will learn how to assess AI-Driven Decision Support Systems within diverse clinical settings, ensuring equitable implementation. Finally, we will discuss the significance of Integrating Social Determinants of Health (SDOH) into ML Models, and how this enhances the accuracy and relevance of healthcare interventions. This session promises insights crucial for leveraging AI and data science to tackle health disparities effectively.
Objectives:
1. Understanding Bias and Fairness in AI/ML Healthcare Applications
2. Evaluating AI-Driven Decision Support Systems in Diverse Clinical Settings
3. Integrating Social Determinants of Health (SDOH) in Machine Learning Models
About the Presenter:
Dr. Luo is Chief AI Officer at Clinical and Translational Sciences Institute (NUCATS) and Institute for Augmented Intelligence in Medicine, and Associate Professor at Department of Preventive Medicine, at Feinberg School of Medicine in Northwestern University. Globally recognized for his leadership and significant contributions to biomedical AI, Dr. Luo has earned the prestigious titles including Fellow of the International Academy of Health Sciences Informatics (IAHSI), Fellow of the American College of Medical Informatics (ACMI) and Fellow of the American Medical Informatics Association (AMIA).
A visionary leader in the field, Dr. Luo is at the forefront of building next-generation informatics and collaborative AI within the healthcare enterprise. His exemplary leadership shapes strategies across various levels, ranging from university settings to entire health systems to national research consortia. With a commitment to democratizing AI literacy, Dr. Luo has been featured in eminent venues such as The Economist, JAMA Network and Becker’s Hospital Review to share unique visions on delivering data and AI strategies that power Research & Development and drive business value.
As a pioneer in the development of multi-modal AI and data science frameworks, Dr. Luo’s work focuses on understanding complex diseases and informing targeted therapies. His groundbreaking research has been featured in leading journals, including JAMA, Nature Medicine, and Nature Biotechnology. Dr. Luo has given numerous keynotes to both academia and industry and has chaired multiple conferences and workshops. With a publication record of over 170 peer-reviewed papers, Dr. Luo’s work has been cited by scientists across more than 30 different countries and 25 research areas.
Dr. Luo’s innovative approach has led to the development of a seminal suite of AI methods based on graph and tensor theory, large language models and reinforcement learning. These methods have been applied in diverse settings, including clinical narratives, disease gene pathways, medical imaging, and predictive modeling with structured clinical data. As a passionate proponent of a paradigm shift from reactive to proactive AI/ML, Dr. Luo’s vision extends to leveraging the new paradigm to automate AI/ML continuous improvement and drive the bench-to-bedside feedback loop. This vision guides the evolution of collaborative AI/ML solutions in complex territories such as drug discovery and highly dynamic situations such as pandemic, positioning Dr. Luo as a leading figure in the field.