Peer Review reports
From: Predictive modeling for COVID-19 readmission risk using machine learning algorithms
| Original Submission | ||
|---|---|---|
| 31 Dec 2021 | Submitted | Original manuscript |
| Resubmission - Version 2 | ||
| Submitted | Manuscript version 2 | |
| 5 Feb 2022 | Reviewed | Reviewer Report |
| 17 Mar 2022 | Reviewed | Reviewer Report - Alessandro Rovetta |
| 10 Apr 2022 | Author responded | Author comments - Hadi Kazemi-Arpanahi |
| Resubmission - Version 3 | ||
| 10 Apr 2022 | Submitted | Manuscript version 3 |
| 12 Apr 2022 | Author responded | Author comments - Hadi Kazemi-Arpanahi |
| Resubmission - Version 4 | ||
| 12 Apr 2022 | Submitted | Manuscript version 4 |
| 13 Apr 2022 | Author responded | Author comments - Hadi Kazemi-Arpanahi |
| Resubmission - Version 5 | ||
| 13 Apr 2022 | Submitted | Manuscript version 5 |
| 14 Apr 2022 | Reviewed | Reviewer Report |
| 17 Apr 2022 | Reviewed | Reviewer Report - Alessandro Rovetta |
| 21 Apr 2022 | Author responded | Author comments - Hadi Kazemi-Arpanahi |
| Resubmission - Version 6 | ||
| 21 Apr 2022 | Submitted | Manuscript version 6 |
| 25 Apr 2022 | Author responded | Author comments - Hadi Kazemi-Arpanahi |
| Resubmission - Version 7 | ||
| 25 Apr 2022 | Submitted | Manuscript version 7 |
| 17 May 2022 | Reviewed | Reviewer Report - Alessandro Rovetta |
| Resubmission - Version 8 | ||
| Submitted | Manuscript version 8 | |
| Publishing | ||
| 18 May 2022 | Editorially accepted | |
| 20 May 2022 | Article published | 10.1186/s12911-022-01880-z |
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