AI-Powered Precision Health: Shaping the Future of Health Care

AI-Powered Precision Health: Shaping the Future of Health Care

Wednesday, Oct. 31, 2018
1 - 2 p.m. Eastern; noon - 1 p.m. Central; 10 - 11 a.m. Pacific

Artificial intelligence (AI) brings both promises and concerns as it filters into the patient care environment, enabling precision health for better outcomes delivered more efficiently. Combining AI methods and systems with an irreplaceable human clinician can advance the delivery of care in a way that outperforms what either can do alone.

Imagine how patient experience would change if we could predict risks of specific outcomes and take proactive action. Thanks to the recent explosion of clinical, genomic and imaging data, a path for precision health — tailoring medical treatment to the individual characteristics of each patient — is becoming possible. Central to precision medicine are artificial intelligence and machine learning (ML), which make sense of the data, helping improve provider efficiency, increase diagnostic accuracy, personalize treatment and drive quality care.

Learn from Nigam Shah, MBBS, PhD, assistant professor of biomedical research and assistant director of the Stanford Center for Biomedical Informatics Research, about Stanford Medicine’s goal for precision health to improve the lives of billions of people. Following his presentation, he will be joined by experts from GE Healthcare for a panel discussion and Q&A exploring how, as health care organizations take advantage of rapid advancements in AI and ML, they will transform the future of health care delivery.

What You Will Learn:

• About a program to bring AI safely and ethically into clinical practice in 3 to 5 years
• How AI and ML can help advance the science of medicine, the practice of medicine and the delivery of health care
• Examples of problems worth solving — use cases in diagnostic, prognostic and therapeutic applications
• How providers will integrate algorithms driven by machine learning, deep learning, natural language processing and other methods into the care process
• How health care organizations, professional societies and other stakeholders must take the lead in ensuring that patient safety, care quality and clinical productivity do not suffer when AI tools are introduced
• How to use machine learning and individual health assessments to better understand the impact of cardiovascular disease, diabetes, cancer, and neurological and mental health
• About a predictive model for palliative care that combines AI with medical expertise to help clinicians make more informed and humane decisions about end-of-life care
   

Speakers:

Nigam H. Shah, MBBS, PhD
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Stanford University

Jeff Hersh, M.D., Ph.D.
Chief Medical Officer
GE Healthcare

Rob Nelson, DBA, MBA, FACHE
Global Marketing Director, AI and Analytics Solutions
GE Healthcare