The Deception of Certainty: how Non-Interpretable Machine Learning Outcomes Challenge the Epistemic Authority of Physicians. A deliberative-relational Approach

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dc.contributor.author Funer, Florian
dc.date.accessioned 2022-11-11T12:41:37Z
dc.date.available 2022-11-11T12:41:37Z
dc.date.issued 2022
dc.identifier.issn 1386-7423
dc.identifier.uri http://hdl.handle.net/10900/132966
dc.language.iso en de_DE
dc.publisher Springer de_DE
dc.relation.uri http://dx.doi.org/10.1007/s11019-022-10076-1 de_DE
dc.subject.ddc 300 de_DE
dc.subject.ddc 900 de_DE
dc.title The Deception of Certainty: how Non-Interpretable Machine Learning Outcomes Challenge the Epistemic Authority of Physicians. A deliberative-relational Approach de_DE
dc.type Article de_DE
utue.quellen.id 20220728000000_00772
utue.publikation.seiten 167-178 de_DE
utue.personen.roh Funer, Florian
dcterms.isPartOf.ZSTitelID Medicine Health Care and Philosophy de_DE
dcterms.isPartOf.ZS-Issue 2 de_DE
dcterms.isPartOf.ZS-Volume 25 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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