Deep Phenotyping of Parkinson’s Disease
Name
jpd_2020_10-3_jpd-10-3-jpd202006_jpd-10-jpd202006.pdf
Description
Published version
Size
855.95 KB
Format
Adobe PDF
Checksum (MD5)
42e64a9110f1b48ce69f75c0e3f904e1
Author(s)
Dorsey, E. Ray
Omberg, Larsson
Waddell, Emma
Adams, Jamie L.
Adams, Roy
Ali, Mohammad Rafayet
Amodeo, Katherine
Arky, Abigail
Augustine, Erika F.
Dinesh, Karthik
Date Issued
July 2020
Journal
Journal of Parkinson's Disease
Publisher
IOS Press
Citation
Dorsey, E. Ray et al. "Deep Phenotyping of Parkinson’s Disease." 10, 3 (July 2020): 855-873 © 2020 IOS Press and the authors
Version
Final published version
Abstract
Phenotype is the set of observable traits of an organism or condition. While advances in genetics, imaging, and molecular biology have improved our understanding of the underlying biology of Parkinson's disease (PD), clinical phenotyping of PD still relies primarily on history and physical examination. These subjective, episodic, categorical assessments are valuable for diagnosis and care but have left gaps in our understanding of the PD phenotype. Sensors can provide objective, continuous, real-world data about the PD clinical phenotype, increase our knowledge of its pathology, enhance evaluation of therapies, and ultimately, improve patient care. In this paper, we explore the concept of deep phenotyping - the comprehensive assessment of a condition using multiple clinical, biological, genetic, imaging, and sensor-based tools - for PD. We discuss the rationale for, outline current approaches to, identify benefits and limitations of, and consider future directions for deep clinical phenotyping.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3233/jpd-202006
