Improving the prediction of patient survival with the aid of residual convolutional neural network (ResNet) in colorectal cancer with unresectable liver metastases treated with bevacizumab-based chemotherapy
In CRC patients with liver metastases treated with BBC, prediction of survival can be improved with the aid of ResNet, enabling optimized individualized treatment.
Authors
- Sung-Hua Chiu (ORCID: https://orcid.org/0000-0003-1118-5541)
- Cheng‐Hsiang Lo (ORCID: https://orcid.org/0000-0001-5002-587X)
- Hsiao-Chi Li (ORCID: https://orcid.org/0000-0003-4527-9730)
- Hsuan‐Hwai Lin (ORCID: https://orcid.org/0000-0003-0171-9044)
- Ping‐Ying Chang (ORCID: https://orcid.org/0000-0002-6526-6606)
- Chao-Cheng Wu
- Wei-Chou Chang
Institutions
- National Taipei University of Technology (TW)
- Tri-Service General Hospital (TW)
- National Defense Medical Center (TW)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s40644-024-00809-1
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- National Science Council
- Tri-Service General Hospital
- National Science and Technology Council