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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Autor principal:	Marco Pellegrini
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/21fd570d2f074c9cb9fa5f6072fc0895
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spelling	oai:doaj.org-article:21fd570d2f074c9cb9fa5f6072fc08952021-12-02T17:55:04ZAccurate prediction of breast cancer survival through coherent voting networks with gene expression profiling10.1038/s41598-021-94243-z2045-2322https://doaj.org/article/21fd570d2f074c9cb9fa5f6072fc08952021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94243-zhttps://doaj.org/toc/2045-2322Abstract 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.Marco PellegriniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Marco Pellegrini Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling
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.
format	article
author	Marco Pellegrini
author_facet	Marco Pellegrini
author_sort	Marco Pellegrini
title	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_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_sort	accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/21fd570d2f074c9cb9fa5f6072fc0895
work_keys_str_mv	AT marcopellegrini accuratepredictionofbreastcancersurvivalthroughcoherentvotingnetworkswithgeneexpressionprofiling
_version_	1718379156155138048

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

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