A Novel Machine Learning Approach for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer: Integration of Multimodal Radiomics With Clinical and Molecular Subtype Markers.
Fatma El-Zahraa A. El-GamalAhmed SharafeldeenEman AlnaghyReham AlghandourNorah Saleh AlghamdiKhadiga M. A. SeddikSameh ShamaaAmal AboueleneenAhmed Elsaid TolbaSamir ElmougyMohammed GhazalSohail ContractorAyman El-BazPublished in: IEEE Access (2024)
Keyphrases
- breast cancer
- machine learning
- dce mri
- bladder cancer
- breast cancer patients
- prognostic factors
- clinical diagnosis
- cancer patients
- breast cancer diagnosis
- cancer treatment
- survival analysis
- early detection
- disease progression
- diagnosis of breast cancer
- logistic regression
- computer aided diagnosis
- mammogram images
- computer aided detection
- medical domain
- outcome prediction
- breast cancer detection
- three dimensional
- text classification
- data mining
- learning algorithm
- cad systems
- clinical data
- bayesian networks
- cross sectional
- model driven
- medical data
- feature selection
- knowledge discovery
- decision trees