Patterns (May 2020)
Physiology as a Lingua Franca for Clinical Machine Learning
- Gopal P. Sarma,
- Erik Reinertsen,
- Aaron Aguirre,
- Chris Anderson,
- Puneet Batra,
- Seung-Hoan Choi,
- Paolo Di Achille,
- Nathaniel Diamant,
- Patrick Ellinor,
- Connor Emdin,
- Akl C. Fahed,
- Samuel Friedman,
- Lia Harrington,
- Jennifer E. Ho,
- Amit V. Khera,
- Shaan Khurshid,
- Marcus Klarqvist,
- Steve Lubitz,
- Anthony Philippakis,
- James Pirruccello,
- Christopher Reeder,
- Collin Stultz,
- Brandon Westover
Affiliations
- Gopal P. Sarma
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts General Hospital, Boston, MA, USA; Corresponding author
- Erik Reinertsen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts General Hospital, Boston, MA, USA; Massachusetts Institute of Technology, Cambridge, MA, USA; Corresponding author
- Aaron Aguirre
- Chris Anderson
- Puneet Batra
- Seung-Hoan Choi
- Paolo Di Achille
- Nathaniel Diamant
- Patrick Ellinor
- Connor Emdin
- Akl C. Fahed
- Samuel Friedman
- Lia Harrington
- Jennifer E. Ho
- Amit V. Khera
- Shaan Khurshid
- Marcus Klarqvist
- Steve Lubitz
- Anthony Philippakis
- James Pirruccello
- Christopher Reeder
- Collin Stultz
- Brandon Westover
- Journal volume & issue
-
Vol. 1,
no. 2
p. 100017
Abstract
The intersection of medicine and machine learning (ML) has the potential to transform healthcare. We describe how physiology, a foundational discipline of medical training and practice with a rich quantitative history, could serve as a starting point for the development of a common language between clinicians and ML experts, thereby accelerating real-world impact.
