Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling
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 t...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-94243-z |
| _version_ | 1819037425280745472 |
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| author | Marco Pellegrini |
| author_facet | Marco Pellegrini |
| author_sort | Marco Pellegrini |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-21T08:21:13Z |
| format | Article |
| id | doaj.art-21fd570d2f074c9cb9fa5f6072fc0895 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-21T08:21:13Z |
| publishDate | 2021-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-21fd570d2f074c9cb9fa5f6072fc08952022-12-21T19:10:25ZengNature PortfolioScientific Reports2045-23222021-07-0111111510.1038/s41598-021-94243-zAccurate prediction of breast cancer survival through coherent voting networks with gene expression profilingMarco Pellegrini0Institute of Informatics and Telematics (IIT), CNRAbstract 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.https://doi.org/10.1038/s41598-021-94243-z |
| spellingShingle | Marco Pellegrini Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling Scientific Reports |
| title | Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| title_full | Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| title_fullStr | Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| title_full_unstemmed | Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| title_short | Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| title_sort | accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling |
| url | https://doi.org/10.1038/s41598-021-94243-z |
| work_keys_str_mv | AT marcopellegrini accuratepredictionofbreastcancersurvivalthroughcoherentvotingnetworkswithgeneexpressionprofiling |