Development of a Predictive model for Parkinson s disease
| dc.contributor.guide | Sachin Ahuja | |
| dc.coverage.spatial | ||
| dc.creator.researcher | Merry Saxena | |
| dc.date.accessioned | 2021-08-31T04:52:56Z | |
| dc.date.available | 2021-08-31T04:52:56Z | |
| dc.date.awarded | 2021 | |
| dc.date.completed | 2021 | |
| dc.date.registered | 2015 | |
| dc.description.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 | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | DVD | |
| dc.format.dimensions | ||
| dc.format.extent | ||
| dc.identifier.uri | http://hdl.handle.net/10603/338320 | |
| dc.language | English | |
| dc.publisher.institution | Faculty of Computer Science | |
| dc.publisher.place | Chandigarh | |
| dc.publisher.university | Chitkara University, Punjab | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Computer Science | |
| dc.subject.keyword | Computer Science Artificial Intelligence | |
| dc.subject.keyword | Engineering and Technology | |
| dc.title | Development of a Predictive model for Parkinson s disease | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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