Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Raphaela Butz"'
Publikováno v:
Human-Centric Intelligent Systems, Vol 4, Iss 2, Pp 286-298 (2024)
Abstract Bayesian networks are commonly used for learning with uncertainty and incorporating expert knowledge. However, they are hard to interpret, especially when the network structure is complex. Methods used to explain Bayesian networks operate un
Externí odkaz:
https://doaj.org/article/84ab2dde3c984a9e9a1daac1f22202e0
Publikováno v:
Artificial Intelligence in Medicine, 134:102438. Elsevier
Artificial Intelligence in Medicine, 134, pp. 1-12
Butz, R, Schulz, R, Hommersom, A & van Eekelen, M 2022, ' Investigating the understandability of XAI methods for enhanced user experience : When Bayesian network users became detectives ', Artificial Intelligence in Medicine, vol. 134, 102438 . https://doi.org/10.1016/j.artmed.2022.102438
Artificial Intelligence in Medicine, 134, 1-12
Artificial Intelligence in Medicine, 134, pp. 1-12
Butz, R, Schulz, R, Hommersom, A & van Eekelen, M 2022, ' Investigating the understandability of XAI methods for enhanced user experience : When Bayesian network users became detectives ', Artificial Intelligence in Medicine, vol. 134, 102438 . https://doi.org/10.1016/j.artmed.2022.102438
Artificial Intelligence in Medicine, 134, 1-12
In the medical domain, the uptake of an AI tool crucially depends on whether clinicians are confident that they understand the tool. Bayesian networks are popular AI models in the medical domain, yet, explaining predictions from Bayesian networks to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::926f1b19684864d2606f6f50ffb8ad12
https://research.ou.nl/en/publications/ca433676-ab08-4726-b8ae-54932ae7211d
https://research.ou.nl/en/publications/ca433676-ab08-4726-b8ae-54932ae7211d
Publikováno v:
STARTPAGE=1;ENDPAGE=11;TITLE=BNAIC/BeNeLearn 2022
Open Universiteit
Butz, R, Hommersom, A, Barenkamp, M & van Ditmarsch, H 2022, ' One counterfactual does not make an explanation ', Paper presented at BNAIC/BeNeLearn 2022, Mechelen, Belgium, 7/11/22-9/11/22 pp. 1-11 . < https://bnaic2022.uantwerpen.be/BNAICBeNeLearn_2022_submission_6245 >
Open Universiteit
Butz, R, Hommersom, A, Barenkamp, M & van Ditmarsch, H 2022, ' One counterfactual does not make an explanation ', Paper presented at BNAIC/BeNeLearn 2022, Mechelen, Belgium, 7/11/22-9/11/22 pp. 1-11 . < https://bnaic2022.uantwerpen.be/BNAICBeNeLearn_2022_submission_6245 >
Counterfactual explanations gained popularity in artificialintelligence over the last years. It is well-known that it is possible togenerate counterfactuals from causal Bayesian networks, but there is noindication which of them are useful for explana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1d757d28fd459344b95e139a9b9ebc76
https://bnaic2022.uantwerpen.be/BNAICBeNeLearn_2022_submission_6245
https://bnaic2022.uantwerpen.be/BNAICBeNeLearn_2022_submission_6245