Synthetic data in medicine: exploring resilience in emerging human-machine relationships

  • This paper explores the multifaceted implications of synthetic data in AI model development, particularly in medical contexts such as oncology. It examines the benefits of synthetic data, including privacy enhancement and bias reduction, but also highlights the associated risks, such as data loss and bias exacerbation. The paper discusses the ethical considerations and proposes strategies to ensure resilience in human-machine relationships, especially in oncology.

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Metadaten
Author:Paula ZiethmannGND, Sarah FriedrichGND, Kerstin Schlögl-FlierlORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1132750
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/113275
ISSN:1614-0702OPAC
ISSN:1862-2607OPAC
Parent Title (German):Datenschutz und Datensicherheit - DuD
Publisher:Springer
Place of publication:Berlin
Type:Article
Language:English
Year of first Publication:2024
Publishing Institution:Universität Augsburg
Release Date:2024/06/03
Volume:48
Issue:6
First Page:358
Last Page:363
DOI:https://doi.org/10.1007/s11623-024-1926-x
Institutes:Katholisch-Theologische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät
Katholisch-Theologische Fakultät / Systematische Theologie
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik
Katholisch-Theologische Fakultät / Systematische Theologie / Lehrstuhl für Moraltheologie
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik / Lehrstuhl für Mathematical Statistics and Artificial Intelligence in Medicine
Dewey Decimal Classification:1 Philosophie und Psychologie / 10 Philosophie / 100 Philosophie und Psychologie
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)