Medical Disease Classification using Machine Learning and Deep Learning
| dc.contributor.guide | Tripathi, Rajeev K. | |
| dc.coverage.spatial | Engineering | |
| dc.creator.researcher | Purwar, Sikha | |
| dc.date.accessioned | 2023-02-15T05:49:07Z | |
| dc.date.available | 2023-02-15T05:49:07Z | |
| dc.date.awarded | 2021 | |
| dc.date.completed | 2021 | |
| dc.date.registered | 2016 | |
| dc.description.abstract | newline Data analysis techniques have succeeded in improving the health of patients due to newlineearly and easy detection of the disease. Without data analysis techniques, detecting newlinethe disease depends entirely on the ability of doctors. This can create a problem in areas newlinewhere there are no good and qualified doctors that can lead to the death of the diseased newlineperson. To address the above challenges, data analysis techniques are now being used newlinein many medical disease detection problem. This thesis presents three different disease newlinedetection approaches. All three disease detection models use data analysis techniques newlinesuch as machine learning (ML) and deep learning (DL). | |
| dc.description.note | Bibliography 86-101 | |
| dc.format.accompanyingmaterial | CD | |
| dc.format.dimensions | ||
| dc.format.extent | 101 | |
| dc.identifier.uri | http://hdl.handle.net/10603/458008 | |
| dc.language | English | |
| dc.publisher.institution | Electronics and Communication Engineering | |
| dc.publisher.place | New Delhi | |
| dc.publisher.university | National Institute of Technology Delhi | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Computer Science | |
| dc.subject.keyword | Computer Science Interdisciplinary Applications | |
| dc.subject.keyword | Engineering and Technology | |
| dc.title | Medical Disease Classification using Machine Learning and Deep Learning | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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