Frontiers in Precision Medicine IV: Artificial Intelligence, Assembling Large Cohorts, and the Population Data Revolution

18 Pages Posted: 9 Dec 2019 Last revised: 16 Jan 2020

See all articles by Adam Bress

Adam Bress

University of Utah Health

Rich Albrechtsen

affiliation not provided to SSRN

Monika Baker

affiliation not provided to SSRN

Jorge L. Contreras

University of Utah - S.J. Quinney College of Law

Zachary Fica

University of Utah Health

Austin Gamblin

University of Utah Health

Chelsea Ratcliff

University of Utah

Bianca Rich

University of Utah Health

Matt Szaniawski

University of Utah Health

Alyssa Thorman

University of Utah Health

Chad Hilton Vansant-Webb

University of Utah Health

Willard Dere

University of Utah - School of Medicine

Date Written: November 21, 2019

Abstract

Large cohort studies and more recently electronic medical records (EMR) are being used to collect massive amounts of genetic information. Implementation of artificial intelligence has become increasingly necessary to interpret this data with the goal of augmenting patient care. While it is impossible to predict what the future holds, policy makers are challenged to create guiding principles and responsibly roll out these new technologies. On March 22, 2019, the University of Utah hosted its fourth annual Precision Medicine Symposium focusing on artificial intelligence, assembling large cohorts, and the population data revolution. The symposium brought together experts in medicine, science, law and ethics to discuss and debate these emerging issues.

Keywords: precision medicine, personalized medicine, genomics, genetics, ai, artificial intelligence, cohort

Suggested Citation

Bress, Adam and Albrechtsen, Rich and Baker, Monika and Contreras, Jorge L. and Fica, Zachary and Gamblin, Austin and Ratcliff, Chelsea and Rich, Bianca and Szaniawski, Matt and Thorman, Alyssa and Hilton Vansant-Webb, Chad and Dere, Willard, Frontiers in Precision Medicine IV: Artificial Intelligence, Assembling Large Cohorts, and the Population Data Revolution (November 21, 2019). University of Utah College of Law Research Paper No. 347, Available at SSRN: https://ssrn.com/abstract=3491307 or http://dx.doi.org/10.2139/ssrn.3491307

Adam Bress

University of Utah Health ( email )

Salt Lake City, UT
United States

Rich Albrechtsen

affiliation not provided to SSRN

Monika Baker

affiliation not provided to SSRN

Jorge L. Contreras (Contact Author)

University of Utah - S.J. Quinney College of Law ( email )

383 S. University Street
Salt Lake City, UT 84112-0730
United States

Zachary Fica

University of Utah Health ( email )

Salt Lake City, UT
United States

Austin Gamblin

University of Utah Health ( email )

Salt Lake City, UT
United States

Chelsea Ratcliff

University of Utah ( email )

1645 E. Campus Center
Salt Lake City, UT 84112
United States

Bianca Rich

University of Utah Health ( email )

Salt Lake City, UT
United States

Matt Szaniawski

University of Utah Health ( email )

Salt Lake City, UT
United States

Alyssa Thorman

University of Utah Health ( email )

Salt Lake City, UT
United States

Chad Hilton Vansant-Webb

University of Utah Health ( email )

Salt Lake City, UT
United States

Willard Dere

University of Utah - School of Medicine ( email )

Salt Lake City, UT
United States

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