Systematic Machine Learning Algorithm for Rapid Thrombosis Detection

The goal of this clinical trial is to compare the use of a machine learning-based algorithm and point-of-care D-dimer to laboratory D-dimer and compression ultrasound to exclude deep vein thrombosis in the under extremities in patients referred to a medical department suspected of having deep vein thrombosis. The main aim is to answer are if a machine learning algorithm and point of care D-dimer can exclude deep vein thrombosis in more patients than clinical assessment and D-dimer alone.

Inclusion Criteria: * Patients referred to the ED due to suspicion of DVT * Age ≥ 18 years * Able to give informed consent Exclusion Criteria: * Ongoing use of anticoagulation for more than 72 hours * Previous participation in the study * Life expectancy of less than three months.