U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19
The rapid increase of patients with coronavirus disease 2019 (COVID-19) has introduced major challenges to healthcare services worldwide. Therefore, fast and accurate clinical assessment of COVID-19 progression and mortality is vital for the management of COVID-19 patients. We developed an automated...
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Veröffentlicht in: | Scientific reports 2021-04, Vol.11 (1), p.9263-9263, Article 9263 |
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Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The rapid increase of patients with coronavirus disease 2019 (COVID-19) has introduced major challenges to healthcare services worldwide. Therefore, fast and accurate clinical assessment of COVID-19 progression and mortality is vital for the management of COVID-19 patients. We developed an automated image-based survival prediction model, called U-survival, which combines deep learning of chest CT images with the established survival analysis methodology of an elastic-net Cox survival model. In an evaluation of 383 COVID-19 positive patients from two hospitals, the prognostic bootstrap prediction performance of U-survival was significantly higher (P |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-021-88591-z |