Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.
Journal:
Scientific reports
Published Date:
Jul 19, 2021
Abstract
For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is hard, due to the heterogeneous nature of the disease. We devised a methodology for predicting 5-years survival based on the new machine learning paradigm of coherent voting networks, with improved accuracy over state-of-the-art prediction methods. The 'coherent voting communities' metaphor provides a certificate justifying the survival prediction for an individual patient, thus facilitating its acceptability in practice, in the vein of explainable Artificial Intelligence. The method we propose is quite flexible and applicable to other types of cancer.
Authors
Keywords
Artificial Intelligence
Biomarkers, Tumor
Breast Neoplasms
Chemotherapy, Adjuvant
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Machine Learning
Mastectomy
Microarray Analysis
Neoplasm Recurrence, Local
Neural Networks, Computer
Predictive Value of Tests
Prognosis
Survival Analysis
Transcriptome