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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.

Titel:	Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.
Autor/in / Beteiligte Person:	Pellegrini, M
Link:	Full Text Finder (Volltext)
Zeitschrift:	Scientific reports, Jg. 11 (2021-07-19), Heft 1, S. 14645
Veröffentlichung:	London : Nature Publishing Group, copyright 2011-, 2021
Medientyp:	academicJournal
ISSN:	2045-2322 (electronic)
DOI:	10.1038/s41598-021-94243-z
Schlagwort:	Artificial Intelligence Biomarkers, Tumor analysis Biomarkers, Tumor genetics Breast Neoplasms genetics Breast Neoplasms pathology Breast Neoplasms therapy Chemotherapy, Adjuvant statistics & numerical data Female Gene Expression Profiling statistics & numerical data Gene Expression Regulation, Neoplastic drug effects Gene Regulatory Networks drug effects Humans Mastectomy statistics & numerical data Microarray Analysis Neoplasm Recurrence, Local genetics Neoplasm Recurrence, Local mortality Neoplasm Recurrence, Local prevention & control Predictive Value of Tests Prognosis Survival Analysis Breast Neoplasms mortality Machine Learning Neoplasm Recurrence, Local diagnosis Neural Networks, Computer Transcriptome drug effects
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article; Validation Study Language: English [Sci Rep] 2021 Jul 19; Vol. 11 (1), pp. 14645. <i>Date of Electronic Publication: </i>2021 Jul 19. MeSH Terms: Machine Learning* ; Neural Networks, Computer* ; Transcriptome* / drug effects ; Breast Neoplasms / mortality ; Neoplasm Recurrence, Local / diagnosis ; Artificial Intelligence ; Biomarkers, Tumor / analysis ; Biomarkers, Tumor / genetics ; Breast Neoplasms / genetics ; Breast Neoplasms / pathology ; Breast Neoplasms / therapy ; Chemotherapy, Adjuvant / statistics & numerical data ; Female ; Gene Expression Profiling / statistics & numerical data ; Gene Expression Regulation, Neoplastic / drug effects ; Gene Regulatory Networks / drug effects ; Humans ; Mastectomy / statistics & numerical data ; Microarray Analysis ; Neoplasm Recurrence, Local / genetics ; Neoplasm Recurrence, Local / mortality ; Neoplasm Recurrence, Local / prevention & control ; Predictive Value of Tests ; Prognosis ; Survival Analysis References: Curr Opin Obstet Gynecol. 2011 Feb;23(1):37-43. (PMID: 21500375) ; Clin Cancer Res. 2015 Jan 15;21(2):373-85. (PMID: 25370469) ; Lancet. 2012 Feb 4;379(9814):432-44. (PMID: 22152853) ; Nature. 2002 Jan 31;415(6871):530-6. (PMID: 11823860) ; Br J Cancer. 2009 Oct 20;101(8):1357-64. (PMID: 19755993) ; Sci Rep. 2019 Feb 28;9(1):3106. (PMID: 30816243) ; Eur J Cancer. 2012 Jan;48(1):12-23. (PMID: 21741824) ; Nature. 2013 May 16;497(7449):378-82. (PMID: 23644459) ; BMC Bioinformatics. 2016 Nov 8;17(Suppl 12):372. (PMID: 28185552) ; Cancer Treat Rev. 2014 Apr;40(3):434-44. (PMID: 24138841) ; Breast Cancer Res Treat. 2011 Apr;126(2):407-20. (PMID: 20490655) ; N Engl J Med. 2002 Dec 19;347(25):1999-2009. (PMID: 12490681) ; Breast Cancer Res. 2010;12(5):R85. (PMID: 20946665) ; Sci Rep. 2019 Dec 13;9(1):19107. (PMID: 31836816) ; N Engl J Med. 2004 Dec 30;351(27):2817-26. (PMID: 15591335) ; IEEE Trans Biomed Eng. 2014 May;61(5):1400-11. (PMID: 24759275) ; J Clin Oncol. 2014 Sep 1;32(25):2794-803. (PMID: 25049332) ; Oncotarget. 2016 Sep 27;7(39):64431-64446. (PMID: 26824988) ; CA Cancer J Clin. 2020 Jan;70(1):7-30. (PMID: 31912902) ; Ther Adv Med Oncol. 2019 Mar 19;11:1758835919833519. (PMID: 30911337) ; Ann Oncol. 2020 May;31(5):650-658. (PMID: 32321669) ; Nat Rev Clin Oncol. 2016 Nov;13(11):674-690. (PMID: 27184417) ; Nature. 2000 Aug 17;406(6797):747-52. (PMID: 10963602) ; Bull Inst Natl Hyg. 1946 Jan-Mar;1:12-7. (PMID: 20986738) ; Cancer Res. 2019 Jul 1;79(13):3466-3478. (PMID: 31048497) ; J Natl Cancer Inst. 2009 May 20;101(10):736-50. (PMID: 19436038) ; PLoS One. 2011;6(12):e28403. (PMID: 22220191) ; Breast Cancer Res. 2015 Jan 27;17:11. (PMID: 25848861) ; Breast Cancer Res. 2011 Oct 06;13(5):R97. (PMID: 21978456) ; J Clin Oncol. 2012 May 20;30(15):1879-87. (PMID: 22454417) ; Clin Cancer Res. 2011 May 1;17(9):2874-84. (PMID: 21415224) ; Oncotarget. 2016 Oct 4;7(40):65024-65033. (PMID: 27542253) ; Bioinformatics. 2008 Dec 15;24(24):2921-2. (PMID: 18953044) ; Breast Cancer Res Treat. 2013 Jan;137(2):407-16. (PMID: 23242614) ; PLoS Comput Biol. 2011 Oct;7(10):e1002240. (PMID: 22028643) ; Eur J Cancer. 2013 Apr;49(6):1374-403. (PMID: 23485231) ; Cancer Commun (Lond). 2019 Apr 29;39(1):22. (PMID: 31030667) ; Br J Cancer. 2012 Aug 21;107(5):793-9. (PMID: 22850551) ; J Clin Oncol. 2010 Apr 10;28(11):1813-20. (PMID: 20231686) ; Artif Intell Med. 2000 Aug;20(1):59-75. (PMID: 11185421) ; Nature. 2012 Apr 18;486(7403):346-52. (PMID: 22522925) ; Signal Transduct Target Ther. 2019 Sep 13;4:34. (PMID: 31637013) Substance Nomenclature: 0 (Biomarkers, Tumor) Entry Date(s): Date Created: 20210720 Date Completed: 20211203 Latest Revision: 20231107 Update Code: 20231215 PubMed Central ID: PMC8289832

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