Advances in diagnosis and prognosis of bacteraemia, bloodstream infection, and sepsis using machine learning: A comprehensive living literature review.

Journal: Artificial intelligence in medicine
PMID: 39705768

Abstract

BACKGROUND: Blood-related infections are a significant concern in healthcare. They can lead to serious medical complications and even death if not promptly diagnosed and treated. Throughout time, medical research has sought to identify clinical factors and strategies to improve the management of these conditions. The increasing adoption of electronic health records has led to a wealth of electronically available medical information and predictive models have emerged as invaluable tools. This manuscript offers a detailed survey of machine-learning techniques used for the diagnosis and prognosis of bacteraemia, bloodstream infections, and sepsis shedding light on their efficacy, potential limitations, and the intricacies of their integration into clinical practice.

Authors

  • Hernandez B
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK. Electronic address: b.hernandez-perez@imperial.ac.uk.
  • Ming D K
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK.
  • Rawson T M
    NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK.
  • Bolton W
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK; NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK; AI4Health Centre for Doctoral Training, Imperial College London, London, UK.
  • Wilson R
    NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK; Department of Global Health and Infectious Diseases, University of Liverpool, Liverpool, UK.
  • Vasikasin V
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK; NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK.
  • Daniels J
    Centre for Bio-Inspired Technology, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
  • Rodriguez-Manzano J
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK; NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK.
  • Davies F J
    Imperial College Healthcare NHS Trust, Praed Street, London, W2 1NY, UK.
  • Georgiou P
    Centre for Bio-Inspired Technology, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
  • Holmes A H
    Centre for Antimicrobial Optimisation, Imperial College London, London, W12 0NN, UK; NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, W12 0NN, UK; Department of Global Health and Infectious Diseases, University of Liverpool, Liverpool, UK.

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