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Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling

Authors: Pellegrini M;

Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling

Abstract

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.

Keywords

Science, Breast Neoplasms, Article, Machine Learning, Breast cancer, Artificial Intelligence, Predictive Value of Tests, Biomarkers, Tumor, Humans, Gene Regulatory Networks, Mastectomy, Survival prediction, Gene Expression Profiling, Q, R, Microarray Analysis, Prognosis, Survival Analysis, Gene Expression Regulation, Neoplastic, Chemotherapy, Adjuvant, Medicine, Female, Neural Networks, Computer, Neoplasm Recurrence, Local, Transcriptome

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
Green
gold
Related to Research communities
Cancer Research