Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers
Conclusions: The risk prediction model for mortality for patients with severe COVID-19 was constructed by the LR algorithm using only hematological parameters in this study. The model contributes to the timely and accurate stratification and management of patients with severe COVID-19.
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Canadian Journal of Infectious Diseases and Medical Microbiology |
| Online Access: | http://dx.doi.org/10.1155/cjid/6606842 |
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| _version_ | 1850263574614638592 |
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| author | Rongrong Dong Han Yao Taoran Chen Wenjing Yang Qi Zhou Jiancheng Xu |
| author_facet | Rongrong Dong Han Yao Taoran Chen Wenjing Yang Qi Zhou Jiancheng Xu |
| author_sort | Rongrong Dong |
| collection | DOAJ |
| description | Conclusions: The risk prediction model for mortality for patients with severe COVID-19 was constructed by the LR algorithm using only hematological parameters in this study. The model contributes to the timely and accurate stratification and management of patients with severe COVID-19. |
| format | Article |
| id | doaj-art-87d44f82562148e6af2ef906da3c0d92 |
| institution | OA Journals |
| issn | 1918-1493 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Canadian Journal of Infectious Diseases and Medical Microbiology |
| spelling | doaj-art-87d44f82562148e6af2ef906da3c0d922025-08-20T01:54:57ZengWileyCanadian Journal of Infectious Diseases and Medical Microbiology1918-14932025-01-01202510.1155/cjid/6606842Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological MarkersRongrong Dong0Han Yao1Taoran Chen2Wenjing Yang3Qi Zhou4Jiancheng Xu5Department of Laboratory MedicineDepartment of Laboratory MedicineDepartment of Laboratory MedicineDepartment of Laboratory MedicineDepartment of PediatricsDepartment of Laboratory MedicineConclusions: The risk prediction model for mortality for patients with severe COVID-19 was constructed by the LR algorithm using only hematological parameters in this study. The model contributes to the timely and accurate stratification and management of patients with severe COVID-19.http://dx.doi.org/10.1155/cjid/6606842 |
| spellingShingle | Rongrong Dong Han Yao Taoran Chen Wenjing Yang Qi Zhou Jiancheng Xu Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers Canadian Journal of Infectious Diseases and Medical Microbiology |
| title | Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers |
| title_full | Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers |
| title_fullStr | Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers |
| title_full_unstemmed | Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers |
| title_short | Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers |
| title_sort | machine learning based prediction of in hospital mortality in severe covid 19 patients using hematological markers |
| url | http://dx.doi.org/10.1155/cjid/6606842 |
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