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Der Unfallchirurg|June 7, 2018
[Successful prehospital emergency thoracotomy after blunt thoracic trauma : Case report and lessons learned]Janosch Dahmen, Marko Brade, Christian Gerach, et al.Der Anaesthesist|November 27, 2020
[COVID-19 Stress test for ensuring emergency healthcare: strategy and response of emergency medical services in Berlin]Janosch Dahmen, Linnart Bäker, Florian Breuer, et al.Journal of Medical Internet Research|March 5, 2020
The Economic Impact of Artificial Intelligence in Health Care: Systematic ReviewJustus Wolff, Josch Pauling, Andreas Keck, et al.Frontiers in Digital Health|October 29, 2021
Success Factors of Artificial Intelligence Implementation in HealthcareJustus Wolff, Josch Pauling, Andreas Keck, et al.Medizinische Klinik, Intensivmedizin Und Notfallmedizin|September 25, 2024
Regional differences, repeated use, and costs of emergency medical services in GermanyMartin Roessler, Claudia Schulte, Christoph Bobeth, et al.BMC Medical Education|January 16, 2010
Job requirements compared to medical school education: differences between graduates from problem-based learning and conventional curriculaChristopher L Schlett, Hinnerk Doll, Janosch Dahmen, et al.Medizinische Klinik, Intensivmedizin Und Notfallmedizin|April 28, 2025
[Onboarding in emergency medicine : Methods, challenges and opportunities]Robert Girshausen, Sebastian Graf, Theresa Holz, et al.Proceedings of the National Academy of Sciences of the United States of America|January 6, 2025
Transforming literature screening: The emerging role of large language models in systematic reviewsFernando M Delgado-Chaves, Matthew J Jennings, Antonio Atalaia, et al.Journal of Integrative Bioinformatics|September 2, 2022
Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scoresJustus Wolff, Julian Matschinske, Dietrich Baumgart, et al.Pageof 2