Artificial intelligence-powered chest computed tomography analysis unveils prognostic insights for COVID-19 mortality among prevalent hemodialysis patients
Chest CT findings, including lung involvement >2.7% and the presence of pleural effusion, nodular consolidation, and patchy infiltrates, significantly indicated mortality in COVID-19 pneumonia among prevalent hemodialysis patients. AI-assisted CT analysis proved useful in assessing lung involvement extent, showing that even minimal lung involvement can be associated with increased mortality.
Authors
- Eunsil Ko (ORCID: https://orcid.org/0000-0001-5959-5545)
- Do Hyoung Kim (ORCID: https://orcid.org/0000-0002-8664-8830)
- Youn Kyung Kee (ORCID: https://orcid.org/0000-0002-0555-9909)
- Ajin Cho (ORCID: https://orcid.org/0000-0001-7097-7026)
- Hayne Cho Park (ORCID: https://orcid.org/0000-0002-1128-3750)
- Sungbong Yu (ORCID: https://orcid.org/0000-0002-1989-6121)
- Eunji Kim (ORCID: https://orcid.org/0000-0002-1306-4105)
- Young-Ki Lee
- K. S. Shon
- Jooyeon Yoon
- Soo-Jin Yoon
Institutions
- Hallym University (KR)
- Hallym University Kangnam Sacred Heart Hospital (KR)
- Kangdong Sacred Heart Hospital (KR)
- National Medical Center (KR)
Publication Details
- Journal
- Kidney Research and Clinical Practice
- Published
- 2024-09-26
- DOI
- https://doi.org/10.23876/j.krcp.24.079
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00