Wavelet Scattering of RhoB-Expressed Deep-Learning Features for Rectal Cancer Prognosis
- Resource Type
- Conference
- Authors
- Pham, Tuan D.; Sun, Xiao-Feng
- Source
- 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) Biomedical Imaging (ISBI), 2023 IEEE 20th International Symposium on. :1-4 Apr, 2023
- Subject
- Bioengineering
Computing and Processing
Photonics and Electrooptics
Signal Processing and Analysis
Proteins
Protein engineering
Scattering
Signal processing
Feature extraction
Prognostics and health management
Artificial intelligence
Rectal cancer
prognosis
IHC imaging
RhoB
wavelet scattering
deep learning
- Language
- ISSN
- 1945-8452
Association between RhoB protein expression and rectal cancer in radiotherapy (RT) resistance has been hypothesized. However, there is no strong clinical evidence to confirm the prognostic power of the protein in this disease. Here, we combine advanced artificial intelligence and signal processing methods to examine RhoB expression captured by immunohistochemical imaging of tumor tissue in a cohort of rectal cancer patients with preoperative RT. Prediction results obtained from the proposed approach with 10-fold cross-validation accuracy rates between 85% and 94% not only discover the potential role of RhoB for rectal cancer prognosis, but also significantly outperform individual pretrained deep-learning models with accuracy between 58% and 67%.