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Deep Phenotyping of Parkinson's Disease
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- Dorsey, E. Ray (author)
- Univ Rochester, Med Ctr, Ctr Hlth Technol, Rochester, NY 14642 USA.;Univ Rochester, Med Ctr, Dept Neurol, Rochester, NY 14642 USA.
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- Omberg, Larsson (author)
- Sage Bionetworks, Seattle, WA USA.
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- Waddell, Emma (author)
- Univ Rochester, Med Ctr, Ctr Hlth Technol, Rochester, NY 14642 USA.
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- Univ Rochester, Med Ctr, Ctr Hlth Technol, Rochester, NY 14642 USA;Univ Rochester, Med Ctr, Dept Neurol, Rochester, NY 14642 USA. Sage Bionetworks, Seattle, WA USA. (creator_code:org_t)
- IOS Press, 2020
- 2020
- English.
- In: Journal of Parkinson's Disease. - : IOS Press. - 1877-7171 .- 1877-718X. ; 10:3, s. 855-873
- Research review (peer-reviewed)
Abstract
Subject headings
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- 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 pheno-typing 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
Keyword
- Autonomic nervous system
- gait
- natural history
- observational study
- Parkinson's disease
- phenotype
- real-world data
- sleep
- smartphone
- social behavior
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