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        - 2025
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                        Mark
        Cohort study of prediction of venous thromboembolism in emergency department patients with extremity symptoms
    
    
- Contribution to journal › Article
 
 - 2024
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                        Mark
        Prior electrocardiograms not useful for machine learning predictions of major adverse cardiac events in emergency department chest pain patients
    
    
- Contribution to journal › Article
 
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                        Mark
        The skåne emergency medicine (SEM) cohort
    
    
- Contribution to journal › Article
 
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                        Mark
        Factors most strongly associated with breathlessness in a population aged 50–64 years
    
    
- Contribution to journal › Article
 
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                        Mark
        The prevalence of clinically relevant delayed intracranial hemorrhage in head trauma patients treated with oral anticoagulants is very low: a retrospective cohort register study
    
    
- Contribution to journal › Article
 
 - 2023
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                        Mark
        Factors important for health-related quality of life in men and women: The population based SCAPIS study
    
    
- Contribution to journal › Article
 
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                        Mark
        Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation
    
    
- Contribution to journal › Article
 
 - 2022
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                        Mark
        Delayed traumatic intracranial haemorrhage : The prevalence is very low in patients on oral anticoagulation
    (2022) Swedish Emergency Medicine Talks 2022
- Contribution to conference › Poster
 
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                        Mark
        Characteristics and severe outcomes of patients presenting to the Emergency Department with dizziness
    (2022) Swedish Emergency Medicine Talks 2022
- Contribution to conference › Poster
 
 - 2021
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                        Mark
        Machine learning compared with rule-in/rule-out algorithms and logistic regression to predict acute myocardial infarction based on troponin T concentrations
    
    
- Contribution to journal › Article
 
 
