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  • 标题:Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling
  • 本地全文:下载
  • 作者:Marco Pellegrini
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2021
  • 卷号:11
  • DOI:10.1038/s41598-021-94243-z
  • 语种:English
  • 出版社:Springer Nature
  • 摘要: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.
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