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AI for Real World Evidence

Yuri Quintana
Fri, 09/01/2023 - 09:12
  • How do we ensure the datasets used to train these systems have equity and diversity?
  • How can you validate the outputs of AI systems?
  • How do you ensure it is not used to intentionally or unintentionally discriminate against people and groups?
  • Whether and how to continue validating such outputs from AI systems with the updates and potential drifts?

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Yuri Quintana Yuri Quintana Administrator
Yuri Quintana
Tue, 09/12/2023 - 13:42

See our panelists for our upcoming meeting.

PANEL 1 - AI FOR REAL-WORLD EVIDENCE:

  • How do we ensure the datasets used to train these systems have equity and diversity?
  • How can you validate the outputs of AI systems?
  • How do you ensure it is not used to intentionally or unintentionally discriminate against people and groups?
  • Whether and how to continue validating such outputs from AI systems with the updates and potential drifts?

Panelists:

  • Mark G. Weiner, MD, FACMI, Deputy CIO for Health System and Research Analytics, Professor of Clinical Population Health Sciences and Medicine, Weill Cornell Medicine, New York-Presbyterian
  • Robert Stolper, Managing Principal, Head of Enterprise Transformation Strategy, IQVIA
  • Sheela Kolluri, PhD, Clinical Domain Lead, Artificial Intelligence, Data & Analytics (AIDA), Pfizer Digital
  • Session Chair: Amar Das, MD, PhD, FACMI, FAMIA, Vice President, Real World Evidence, Guardant Health