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Presentation
Big Data and Parkinson’s Disease: Exploration, Analyses, and Data Challenges
Proceedings of the 51st Hawaii International Conference on System Sciences
  • Mahalakshmi SenthilarumugamVeilukandammal, Iowa State University
  • Sree Nilakanta, Iowa State University
  • Baskar Ganapathysubramanian, Iowa State University
  • Vellareddy Anantharam, Iowa State University
  • Anumantha Kanthasamy, Iowa State University
  • Auriel A. Willette, Iowa State University
Document Type
Conference Proceeding
Conference
51st Hawaii International Conference on System Sciences (HICSS-51)
Publication Version
Published Version
Publication Date
1-1-2018
Conference Date
January 3-6, 2018
Geolocation
(19.9372484, -155.79106809999996)
Abstract

In healthcare, a tremendous amount of clinical and laboratory tests, imaging, prescription and medication data are being collected. Big data analytics on these data aim at early detection of disease which will help in developing preventive measures and in improving patient care. Parkinson disease is the second-most common neurodegenerative disorder in the United States. To find a cure for Parkinson's disease biological, clinical and behavioral data of different cohorts are collected, managed and propagated through Parkinson’s Progression Markers Initiative (PPMI). Applying big data technology to this data will lead to the identification of the potential biomarkers of Parkinson’s disease. Data collected in human clinical studies is imbalanced, heterogeneous, incongruent and sparse. This study focuses on the ways to overcome the challenges offered by PPMI data which is wide and gappy. This work leverages the initial discoveries made through descriptive studies of various attributes. The exploration of data led to identifying the significant attributes. We are further working to build a software suite that enables end to end analysis of Parkinson’s data (from cleaning and curating data, to imputation, to dimensionality reduction, to multivariate correlation and finally to identify potential biomarkers).

Comments

This article is published as SenthilarumugamVeilukandammal, Mahalakshmi, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, Anumantha Kanthasamy, and Auriel A Willette. "Big Data and Parkinson’s Disease: Exploration, Analyses, and Data Challenges." In Proceedings of the 51st Hawaii International Conference on System Sciences. 2018. Posted with permission.

Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 4.0
Language
en
File Format
application/pdf
Citation Information
Mahalakshmi SenthilarumugamVeilukandammal, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, et al.. "Big Data and Parkinson’s Disease: Exploration, Analyses, and Data Challenges" Waikoloa Village, HIProceedings of the 51st Hawaii International Conference on System Sciences (2018) p. 2778 - 2783
Available at: http://works.bepress.com/baskar-ganapathysubramanian/56/