Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/338320
Title: | Development of a Predictive model for Parkinson s disease |
Researcher: | Merry Saxena |
Guide(s): | Sachin Ahuja |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | Chitkara University, Punjab |
Completed Date: | 2021 |
Abstract: | Parkinson s Disease is the second most prominent chronic neurological disorder / disease newlineafter Alzheimer s dementia. The major concern is the early detection and progression of newlinethe disease which grossly affects the life in disability adjusted years. Since the newlineprogression of this disease is high heterogenous in nature across the patients, there is a newlineneed to aid the clinician to properly understand and predict the unforeseen circumstances newlineusing information technology tools. In this thesis, we address these challenges for newlineParkinson s disease (PD), using machine learning algorithm -quantum neural network. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/338320 |
Appears in Departments: | Faculty of Computer Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
80_recommendation.pdf | Attached File | 305.71 kB | Adobe PDF | View/Open |
abstract_ merry saxena.pdf | 350.44 kB | Adobe PDF | View/Open | |
certificate_ merry saxena.pdf | 1.03 MB | Adobe PDF | View/Open | |
chapter 1_ merry thesis.pdf | 890.06 kB | Adobe PDF | View/Open | |
chapter 3_merry thesis.pdf | 1.13 MB | Adobe PDF | View/Open | |
chapter 4_merry thesis.pdf | 605.74 kB | Adobe PDF | View/Open | |
chapter 5_merry thesis.pdf | 870.26 kB | Adobe PDF | View/Open | |
chapter 6_merry thesis.pdf | 117.17 kB | Adobe PDF | View/Open | |
preliminary pages_ merry saxena.pdf | 1.09 MB | Adobe PDF | View/Open | |
references.pdf | 348.43 kB | Adobe PDF | View/Open |
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