Machine learning to predict COVID-19 outcomes to facilitate decision
making
- Sonu Subudhi,
- Ashish Verma,
- Ankit Patel
Abstract
An increasing number of COVID-19 cases worldwide has overwhelmed the
healthcare system. Physicians are struggling to allocate resources and
to focus their attention on high-risk patients, partly because early
identification of high-risk individuals is difficult. This can be
attributed to the fact that COVID-19 is a novel disease and its
pathogenesis is still partially understood. However, machine learning
algorithms have the capability to correlate a large number of parameters
within a short period of time to identify the predictors of disease
outcome. Implementing such an algorithm to predict high-risk individuals
during the early stages of infection, would be helpful in decision
making for clinicians. Here, we propose recommendations to integrate
machine learning model with electronic health records so that a
real-time risk score can be developed for COVID-19.06 Jun 2020Submitted to International Journal of Clinical Practice 06 Jun 2020Submission Checks Completed
06 Jun 2020Assigned to Editor
07 Jun 2020Reviewer(s) Assigned
20 Jun 2020Review(s) Completed, Editorial Evaluation Pending
24 Jun 20201st Revision Received
16 Jul 2020Submission Checks Completed
16 Jul 2020Assigned to Editor
16 Jul 2020Reviewer(s) Assigned
03 Aug 2020Review(s) Completed, Editorial Evaluation Pending
05 Aug 20202nd Revision Received
05 Aug 2020Submission Checks Completed
05 Aug 2020Assigned to Editor
05 Aug 2020Reviewer(s) Assigned
10 Aug 2020Review(s) Completed, Editorial Evaluation Pending
11 Aug 20203rd Revision Received
11 Aug 2020Submission Checks Completed
11 Aug 2020Assigned to Editor
13 Aug 2020Review(s) Completed, Editorial Evaluation Pending
16 Aug 2020Editorial Decision: Accept