[Machine learning in anesthesiology]

Anaesthesist. 2020 Aug;69(8):535-543. doi: 10.1007/s00101-020-00764-z.
[Article in German]

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.

Keywords: Artificial intelligence; Big data; Medical decision making, computer-assisted; Personalized medicine; Risk prediction.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Anesthesiology*
  • Artificial Intelligence*
  • Humans
  • Machine Learning*
  • Neural Networks, Computer
  • Precision Medicine