1 – 10 of 80
- show: 10
- |
- sort: year (new to old)
Close
Embed this list
<iframe src=""
width=""
height=""
allowtransparency="true"
frameborder="0">
</iframe>
- 2025
-
Mark
Making Sense of Medical AI : AI transparency and the configuration of expertise
(2025)
- Thesis › Doctoral thesis (compilation)
-
Mark
Cohort study of prediction of venous thromboembolism in emergency department patients with extremity symptoms
- Contribution to journal › Article
-
Mark
Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden
- Contribution to journal › Article
-
Mark
Transfer learning for predicting acute myocardial infarction using electrocardiograms
- Contribution to journal › Article
- 2024
-
Mark
Effectiveness and Safety of the ESC-TROP (European Society of Cardiology 0h/1h Troponin Rule-Out Protocol) Trial
- Contribution to journal › Article
-
Mark
Exploring Artificial Intelligence in Emergency Medicine for Predicting Disposition, Death, and Diagnosis
(2024) In Lund University, Faculty of Medicine Doctoral Dissertation Series
- Thesis › Doctoral thesis (compilation)
-
Mark
Engaging with artificial intelligence in Mammography Screening : Swedish breast radiologists’ views on trust, information and expertise
- Contribution to journal › Article
-
Mark
Navigating Health Applications Realms : Consent Challenges and User Empowerment in European Law
(2024) 10th EAI International Conference on IoT Technologies for Health-Care, HealthyIoT 2023, and 4th EAI International Conference on Wearables in Healthcare, HealthWear 2023 In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST 530 LNICST. p.117-130
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
-
Mark
How does an AI diagnose dyspnoea in ED triage without human guidance?
(2024) Swedish Emergency Medicine Talks - SWEETS24
- Contribution to conference › Poster
-
Mark
Factors most strongly associated with breathlessness in a population aged 50–64 years
- Contribution to journal › Article
