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Artificial Intelligence in Critical Care

The Path from Promise to Practice

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Artificial Intelligence in Medicine

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Abstract

The hectic domain of critical care is, arguably, one of the most demanding instances of multidisciplinary medical decision-making. It is also a domain infused with monitoring and life-sustaining technologies that leave behind the type of digital data trail that is ideal for the deployment of artificial intelligence and, particularly, machine learning methods and analytical pipelines. These data analysis methods should provide medical decision support to intensivists, but there is yet no clear framework or standard set of guidelines on how to do so. In this chapter, we aim to provide readers with information on the current landscape of applications of machine learning in critical care and also with a clear outline of some of the many challenges yet to overcome to guarantee the success of such applications, including the problem of model interpretability and explainability, the technology compliance with current legislation, or the education of medical practitioners in the area of data analytics using open-source software.

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Author information

Authors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Alfredo Vellido

  2. Intelligent Data Science and Artificial Intelligence (IDEAI-UPC) Research Center, Barcelona, Spain

    Alfredo Vellido

  3. Eurecat, Barcelona, Spain

    Vicent Ribas

Authors
  1. Alfredo Vellido
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  2. Vicent Ribas
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Corresponding author

Correspondence to Alfredo Vellido .

Editor information

Editors and Affiliations

  1. Karolinska Institute, Stockholm, Sweden

    Niklas Lidströmer

  2. Faculty of Medicine, Imperial College London, London, UK

    Hutan Ashrafian

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Vellido, A., Ribas, V. (2021). Artificial Intelligence in Critical Care. In: Lidströmer, N., Ashrafian, H. (eds) Artificial Intelligence in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-58080-3_174-1

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  • DOI: https://doi.org/10.1007/978-3-030-58080-3_174-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58080-3

  • Online ISBN: 978-3-030-58080-3

  • eBook Packages: Springer Reference MedicineReference Module Medicine

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