A Machine Learning-Based Clustering Using Radiomics of F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography for the Prediction of Prognosis in Patients with Intrahepatic Cholangiocarcinoma
This study demonstrated that machine learning-based PET radiomics clustering can preoperatively predict prognosis and provide valuable information complementing the genomic profiling of IHCC.
Authors
- Hannah Kim (ORCID: https://orcid.org/0000-0001-7138-6623)
- Rosie Kwon (ORCID: https://orcid.org/0000-0001-5422-4446)
- Bong‐Il Song (ORCID: https://orcid.org/0000-0002-3106-6112)
- Kyoung Sook Won (ORCID: https://orcid.org/0000-0001-7185-911X)
- Koo Jeong Kang (ORCID: https://orcid.org/0000-0003-1385-8308)
- Keun Soo Ahn (ORCID: https://orcid.org/0000-0001-8738-8009)
- Hae Won Kim (ORCID: https://orcid.org/0000-0002-6707-3904)
- Jinny Lee (ORCID: https://orcid.org/0000-0001-5515-1971)
- Hye Won Lee (ORCID: https://orcid.org/0000-0001-8540-524X)
- Yong‐Hoon Kim (ORCID: https://orcid.org/0000-0001-9968-645X)
- Tae-Seok Kim
Institutions
- Keimyung University (KR)
- Columbia University (US)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-10-08
- DOI
- https://doi.org/10.3390/diagnostics14192245
- Citations
- 3
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.72