[Machine learning in anesthesiology].

Journal: Der Anaesthesist
Published Date:

Abstract

The application of artificial intelligence (AI) is currently changing very different areas of life. Artificial intelligence involves the emulation of human behavior with the aid of methods from mathematics and informatics. Machine learning (ML) represents a subdivision of AI. Algorithms for ML have the potential to optimize patient care, in that they can be utilized in a supportive way in personalized medicine, decision making and risk prediction. Although the majority of the applications in medicine are still limited to data analysis and research, it is certain that ML will become increasingly more important in scientific and clinical aspects in this supportive function. Therefore, it is necessary for clinicians to have at least a basic understanding of the functional principles, strengths and weaknesses of ML.

Authors

  • J Sassenscheidt
    Klinik und Poliklinik für Anästhesiologie, Zentrum für Anästhesiologie und Intensivmedizin, Martinistr. 52, 20246, Hamburg, Deutschland.
  • B Jungwirth
    Klinik für Anästhesiologie, Universitätsklinikum Ulm, 89070, Ulm, Deutschland.
  • J C Kubitz
    Klinik und Poliklinik für Anästhesiologie, Zentrum für Anästhesiologie und Intensivmedizin, Martinistr. 52, 20246, Hamburg, Deutschland. j.kubitz@uke.de.