An interpretable mortality prediction model for COVID-19 patients
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Open Access
- 30 April 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Machine Intelligence
- Vol. 2 (5), 283-+
- https://doi.org/10.1038/s42256-020-0180-7
Abstract
No abstract availableThis publication has 18 references indexed in Scilit:
- Clinical features of patients infected with 2019 novel coronavirus in Wuhan, ChinaThe Lancet, 2020
- A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family clusterThe Lancet, 2020
- From local explanations to global understanding with explainable AI for treesNature Machine Intelligence, 2020
- XGBoostPublished by Association for Computing Machinery (ACM) ,2016
- Aetiology, outcomes & predictors of mortality in acute respiratory distress syndrome from a tertiary care centre in north IndiaIndian Journal of Medical Research, 2016
- Staging of Acute Exacerbation in Patients with Idiopathic Pulmonary FibrosisLung, 2013
- Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptorNature, 2013
- Plasma C-Reactive Protein Levels Are Associated With Improved Outcome in ARDSSocial psychiatry. Sozialpsychiatrie. Psychiatrie sociale, 2009
- Rosuvastatin to Prevent Vascular Events in Men and Women with Elevated C-Reactive ProteinNew England Journal of Medicine, 2008
- Structure of SARS Coronavirus Spike Receptor-Binding Domain Complexed with ReceptorScience, 2005