Machine Learning for Health Informatics

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Buch/BerichtForschungBegutachtung

Abstract

Machine Learning (ML) studies algorithms which can learn from data to gain knowledge from experience and to make decisions and predictions. Health Informatics (HI) studies the effective use of probabilistic information for decision making. The combination of both has greatest potential to rise quality, efficacy and efficiency of treatment and care. Health systems worldwide are confronted with “big data” in high dimensions, where the inclusion of a human is impossible and automatic ML (aML) show impressive results. However, sometimes we are confronted with complex data, “little data”, or rare events, where aML-approaches suffer of insufficient training samples. Here interactive ML (iML) may be of help, particularly with a doctor-in-the-loop, e.g. in subspace clustering, k-Anonymization, protein folding and protein design. However, successful application of ML for HI needs an integrated approach, fostering a concerted effort of four areas: (1) data science, (2) algorithms (with focus on networks and topology (structure), and entropy (time), (3) data visualization, and last but not least (4) privacy, data protection, safety & security.
Originalspracheenglisch
TitelMachine Learning for Health Informatics: State-of-the-Art and Future Challenges, Lecture Notes in Artificial Intelligence LNAI 9605
Redakteure/-innenAndreas Holzinger
ErscheinungsortCham
Herausgeber (Verlag)Springer International
Seiten1-24
ISBN (Print)978-3-319-50477-3
DOIs
PublikationsstatusVeröffentlicht - 22 Dez 2016

Publikationsreihe

NameLecture Notes in Artificial Intelligence
Herausgeber (Verlag)Springer
Band9605

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Schlagwörter

    ASJC Scopus subject areas

    • Artificial intelligence

    Fields of Expertise

    • Information, Communication & Computing

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)
    • Application

    Dieses zitieren

    Holzinger, A. (2016). Machine Learning for Health Informatics. in A. Holzinger (Hrsg.), Machine Learning for Health Informatics: State-of-the-Art and Future Challenges, Lecture Notes in Artificial Intelligence LNAI 9605 (S. 1-24). (Lecture Notes in Artificial Intelligence; Band 9605). Cham: Springer International. https://doi.org/10.1007/978-3-319-50478-0_1