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http://hdl.handle.net/11375/26944
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DC Field | Value | Language |
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dc.contributor.advisor | Jeremic, Aleksandar | - |
dc.contributor.author | Mohan, Aishwarya | - |
dc.date.accessioned | 2021-10-01T15:32:18Z | - |
dc.date.available | 2021-10-01T15:32:18Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/11375/26944 | - |
dc.description.abstract | 5-year survival rate of patients with metastasized non-small cell lung cancer (NSCLC) who received chemotherapy was less than 5% (Kathryn C. Arbour, 2019). Our ability to provide survival status of a patient i.e. Alive or death at any time in future is important from at least two standpoints: a) from clinical standpoint it enables clinicians to provide optimal delivery of healthcare and b) from personal standpoint by providing patient’s family with opportunities to plan their life ahead and potentially cope with emotional aspect of loss of life. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Lung cancer, machine learning | en_US |
dc.title | Predicting survival status of lung cancer patients using machine learning | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Mohan_Aishwarya_2021sept_MASc.pdf | 2.51 MB | Adobe PDF | View/Open |
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