Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/31368
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Snider B | - |
dc.contributor.author | Phillips P | - |
dc.contributor.author | MacLean A | - |
dc.contributor.author | McBean E | - |
dc.contributor.author | Gadsden SA | - |
dc.contributor.author | Yawney J | - |
dc.date.accessioned | 2025-03-03T23:33:06Z | - |
dc.date.available | 2025-03-03T23:33:06Z | - |
dc.date.issued | 2020-09-30 | - |
dc.identifier.uri | http://hdl.handle.net/11375/31368 | - |
dc.subject | 32 Biomedical and Clinical Sciences | - |
dc.subject | 3202 Clinical Sciences | - |
dc.subject | 42 Health Sciences | - |
dc.subject | Machine Learning and Artificial Intelligence | - |
dc.subject | Emerging Infectious Diseases | - |
dc.subject | Coronaviruses | - |
dc.subject | Bioengineering | - |
dc.subject | Infectious Diseases | - |
dc.subject | 3 Good Health and Well Being | - |
dc.title | Artificial intelligence to predict the risk of mortality from Covid-19: Insights from a Canadian Application | - |
dc.type | Article | - |
dc.date.updated | 2025-03-03T23:33:04Z | - |
dc.contributor.department | Mechanical Engineering | - |
dc.identifier.doi | https://doi.org/10.1101/2020.09.29.20201632 | - |
Appears in Collections: | Mechanical Engineering Publications |
Files in This Item:
File | Description | Size | Format | |
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2020.09.29.20201632v1.full.pdf | Published version | 194.67 kB | Adobe PDF | View/Open |
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