[FG] Boeddinghaus Jasper

The research project aims to develop clinical decision support tools integrating established diagnostic variables and machine learning (ML) models for rapid diagnosis of acute life-threatening cardiovascular conditions in emergency department (ED) patients with chest pain or dyspnea with the ultimate goal of Improved diagnostic accuracy, faster patient management, and reduced medical errors.

Prospective, international, multi-centre cohort study that aims to improve the diagnosis of myocardial infarction.

Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) is a validated clinical decision support tool that uses machine learning with or without serial cardiac troponin measurements at a flexible time point to calculate the probability of myocardial infarction (MI).

The High-Sensitivity Troponin in the Evaluation of patients with suspected Acute Coronary Syndrome (High-STEACS) trial is a stepped-wedge, cluster-randomised controlled trial that aimed to prospectively evaluate the implementation of an hs-cTnI assay in consecutive patients with suspected acute coronary syndrome in ten secondary and tertiary care hospitals in Scotland.

The overall objectives of this project are to improve the early diagnosis and management of ACVD. Therefore, this project has two main aims: first, to develop and implement a clinical decision support tool that integrates and visualizes results of established diagnostic variables (e.g., ST-segment elevation in the 12-lead ECG) in a dashboard and, second, to derive and validate human-simulatability machine learning (ML) models that integrate information from the three main diagnostic pillars to rapidly inform the diagnostic probability for six ACVD in patients with acute chest pain and/or acute dyspnoea.

Prospective, international, multi-centre cohort study that aims to understand the importance of myocardial injury and ischemia in patients with rapid atrial fibrillation.

This is a multi-center, prospective, stepped-wedge cluster randomised controlled trial. The aim is a clinical implementation of the European Society of Cardiology 0/1h-algorithm and the evaluation of its safety and efficacy for diagnosis of myocardial infarction compared to current practice.