Nuklearmedizin 2023; 62(06): 332-333
DOI: 10.1055/a-2198-0614
Editorial

AI in Nuclear Medicine – a review of the current situation

KI in der Nuklearmedizin – eine Bestandsaufnahme
Isabelle Miederer
1   Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)
,
Julian Manuel Michael Rogasch
2   Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
3   Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
,
Thomas Wendler
4   Clinical Computational Medical Imaging Research, Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Augsburg, Germany (Ringgold ID: RIN26522)
5   Computer-Aided Medical Procedures and Augmented Reality, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany (Ringgold ID: RIN9184)
› Institutsangaben


Publikationsverlauf

Eingereicht: 29. September 2023

Angenommen: 25. Oktober 2023

Artikel online veröffentlicht:
23. November 2023

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  • References

  • 1 Russakovsky O, Deng J, Su H. et al. ImageNet Large Scale Visual Recognition Challenge. Int J Comput Vis 2015; 115 (03) 211-52
  • 2 OpenAI. Improving language understanding with unsupervised learning. Zugriff am 25. September 2023 unter: https://openai.com/research/language-unsupervised
  • 3 Rogasch JMM, Metzger G, Preisler M. et al. ChatGPT: Can You Prepare My Patients for [(18)F]FDG PET/CT and Explain My Reports?. Journal of nuclear medicine : official publication, Society of Nuclear Medicine 2023;
  • 4 Miederer I, Rogasch JMM, Fischer R. et al. The Medical Informatics Initiative and the Network University Medicine – Perspectives for Nuclear Medicine. Nuklearmedizin Nuclear medicine 2023; 62 (05) 276-283