Andreas HOLZINGER

ORCID iD
https://orcid.org/0000-0002-6786-5194
  • Country
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Austria

Sources:
Andreas HOLZINGER (2016-01-24)

  • Keywords
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Health Informatics,

Sources:
Andreas HOLZINGER (2014-09-28)

Interactive Machine Learning (iML),

Sources:
Andreas HOLZINGER (2014-09-28)

Explainable AI,

Sources:
Andreas HOLZINGER (2014-09-28)

Machine Learning,

Sources:
Andreas HOLZINGER (2015-12-02)

Knowledge Extraction

Sources:
Andreas HOLZINGER (2015-12-02)

  • Websites
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Holzinger Group HCI-KDD

Sources:
Andreas HOLZINGER (2015-11-01)

Andreas Holzinger Homepage

Sources:
Andreas HOLZINGER (2015-11-01)

Andreas Holzinger - Google Scholar

Sources:
Andreas HOLZINGER (2018-01-03)

Andreas Holzinger - DBLP

Sources:
Andreas HOLZINGER (2018-01-03)

  • Other IDs
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ResearcherID: E-9530-2010

Sources:
ResearcherID (2014-01-22)

Scopus Author ID: 23396282000

Sources:
Scopus - Elsevier (2015-08-09)

Loop profile: 130182

Sources:
Loop (2015-11-01)

Biography

Andreas Holzinger build a solid track record in machine learning/artificial intelligence & knowledge extraction for health informatics. Particularly, he has been working on integrated machine learning, which is manifested in Holzinger’s HCI-KDD approach. This is based on the idea of combining the best of the two worlds working towards understanding intelligence: Human–Computer Interaction (HCI), rooted in cognitive science, particularly dealing with human intelligence, and Knowledge Discovery/Data Mining (KDD), rooted in computer science, particularly dealing with artificial intelligence. Andreas has pioneered the interactive machine learning approach with the human-in-the-loop, which he proved with his glass-box approach. In light of raising legal and privacy issues in the European Union (General Data Protection Regulation, GDPR) in the future it will become important to make decisions transparent, understandable and retraceable and to explain why a machine decsion has been made – towards explainable artificial intelligence (explainable-ai).
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