Co-design of a clinical decision support tool for use in patients with acute chest pain in the Emergency Department
  Our objective is to reduce 30-day reattendance by a fifth in patients presenting with acute chest pain to the Emergency Room using artificial intelligence tools to augment clinical decisions. To achieve this, we will provide diagnostic probabilities and risks of reattendance and major adverse cardiac events to guide more effective care. We will train and validate deep learning models that integrate routinely collected longitudinal data, cardiac biomarkers, and diagnostic tests in consecutive patients with acute chest pain. We will communicate these probabilities and risks using a platform embedded within the patient record that provides augmented clinical decision support in real-time.

  • Start Date:

    1 August 2022

  • End Date:

    30 April 2023

  • Activity Type:

    Externally Funded Research

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Project Team