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pro vyhledávání: '"ten Teije, A."'
Publikováno v:
In Artificial Intelligence In Medicine September 2019 100
Autor:
Zamborlini, Veruska, da Silveira, Marcos, Pruski, Cedric, ten Teije, Annette, Geleijn, Edwin, van der Leeden, Marike, Stuiver, Martijn, van Harmelen, Frank
Publikováno v:
In Artificial Intelligence In Medicine September 2017 81:78-93
Autor:
Anna Breit, Laura Waltersdorfer, Fajar J. Ekaputra, Marta Sabou, Andreas Ekelhart, Andreea Iana, Heiko Paulheim, Jan Portisch, Artem Revenko, Annette ten Teije, Frank van Harmelen
Publikováno v:
ACM Computing Surveys.
In line with the general trend in artificial intelligence research to create intelligent systems that combine learning and symbolic components, a new sub-area has emerged that focuses on combining machine learning (ML) components with techniques deve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20d7e07f33090838f983a7ab099224c1
https://research.wu.ac.at/de/publications/72e575fb-bccb-4147-a15e-db3bcdc4d07c
https://research.wu.ac.at/de/publications/72e575fb-bccb-4147-a15e-db3bcdc4d07c
Akademický článek
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Autor:
Milian, Krystyna, Hoekstra, Rinke, Bucur, Anca, ten Teije, Annette, van Harmelen, Frank, Paulissen, John
Publikováno v:
In Journal of Biomedical Informatics August 2015 56:205-219
Publikováno v:
The Semantic Web ISBN: 9783031334542
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e166fba09e310df468a7b7ef185067af
https://doi.org/10.1007/978-3-031-33455-9_1
https://doi.org/10.1007/978-3-031-33455-9_1
Akademický článek
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Publikováno v:
In Artificial Intelligence In Medicine February 2013 57(2):91-109
Publikováno v:
The Semantic Web
A meta-analysis is a Science of Science method widely used in the medical and social sciences to review, aggregate and quantitatively synthesise a body of studies that address the same research question. With the volume of research growing exponentia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmc_________::56a0e79aaf3ee43f81e7cf343303eb42
http://europepmc.org/articles/PMC7250615
http://europepmc.org/articles/PMC7250615
Autor:
Jansen, Tom, Geleijnse, Gijs, van Maaren, Marissa, Hendriks, Mathijs P., Ten Teije, Annette, Moncada-Torres, Arturo
Publikováno v:
Jansen, T, Geleijnse, G, van Maaren, M, Hendriks, M P, Ten Teije, A & Moncada-Torres, A 2020, Machine learning explainability in breast cancer survival . in L B Pape-Haugaard, C Lovis, I C Madsen, P Weber, P H Nielsen & P Scott (eds), Digital Personalized Health and Medicine : Proceedings of MIE 2020 . Studies in Health Technology and Informatics, vol. 270, IOS Press, pp. 307-311, 30th Medical Informatics Europe Conference, MIE 2020, Geneva, Switzerland, 28/04/20 . https://doi.org/10.3233/SHTI200172
Machine Learning (ML) can improve the diagnosis, treatment decisions, and understanding of cancer. However, the low explainability of how “black box” ML methods produce their output hinders their clinical adoption. In this paper, we used data fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d14019f452c6a2e0d34f058d2e91dbb0
https://doi.org/10.3233/shti200172
https://doi.org/10.3233/shti200172