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pro vyhledávání: '"Andrea Campagner"'
Autor:
Andrea Campagner, Davide Ciucci
Publikováno v:
Knowledge-Based Systems. 180:51-61
In this work, we introduce the notion of orthopartition as a generalized partition with uncertainty. Several entropy-based measures are then developed to measure this intrinsic uncertainty, which are in turn applied to soft clustering. An application
In recent years, Machine Learning (ML) has attracted wide interest as aid for decision makers in complex domains, such as medicine. Although domain experts are typically aware of the intrinsic uncertainty around it, the issue of Ground Truth (GT) qua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66d7710fba0cf65cb0946344f6d24ece
http://hdl.handle.net/10281/289890
http://hdl.handle.net/10281/289890
Publikováno v:
Modeling Decisions for Artificial Intelligence ISBN: 9783030267728
MDAI
MDAI
Machine learning–based decision support systems (DSS) are attracting the interest of the medical community. Their usage, however, could have deep consequences in terms of biasing the doctor’s interpretation of a case through automation bias and d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c7b1c9ccf9bdbeff34c96288a3defe8
https://doi.org/10.1007/978-3-030-26773-5_18
https://doi.org/10.1007/978-3-030-26773-5_18
Publikováno v:
Rough Sets ISBN: 9783030228149
IJCRS
IJCRS
Ambiguity, that is the lack of information to produce a specific classification, is an important issue in decision–making and supervised classification. In case of ambiguity, human–decision makers can resort to abstaining from making precise clas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::829233c50d0da815a6f6e649b7e007e0
http://hdl.handle.net/10281/265895
http://hdl.handle.net/10281/265895
Publikováno v:
Scopus-Elsevier
HEALTHINF
HEALTHINF
Uncertainty is an intrinsic component of the clinical practice, which manifests itself in a variety of different forms. Despite the growing popularity of Machine Learning-based Decision Support Systems (ML-DSS) in the clinical domain, the effects of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::995aaccec7ca6402c48beb4f417773b6
http://www.scopus.com/inward/record.url?eid=2-s2.0-85064622637&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85064622637&partnerID=MN8TOARS