Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19.
Saved in:
| Title: | Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19. |
|---|---|
| Authors: | Yu L; Department of Pathology, Beaumont Health System, Royal Oak, MI, United States of America., Halalau A; Department of Internal Medicine, Beaumont Health System, Royal Oak, MI, United States of America., Dalal B; Division of Pulmonary and Critical Care Medicine, Beaumont Health System, Royal Oak, MI, United States of America., Abbas AE; Department of Cardiovascular Medicine, Beaumont Health System, Royal Oak, MI, United States of America., Ivascu F; Department of General Surgery, Beaumont Health System, Royal Oak, MI, United States of America., Amin M; Department of Pathology, Beaumont Health System, Royal Oak, MI, United States of America., Nair GB; Division of Pulmonary and Critical Care Medicine, Beaumont Health System, Royal Oak, MI, United States of America. |
| Source: | PloS one [PLoS One] 2021 Apr 01; Vol. 16 (4), pp. e0249285. Date of Electronic Publication: 2021 Apr 01 (Print Publication: 2021). |
| Publication Type: | Journal Article; Multicenter Study |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1932-6203 |
|---|---|
| DOI: | 10.1371/journal.pone.0249285 |
