Rückverfolgbarkeit für künstliche Intelligenz: Umsetzung einer Traceability-Strategie bei der modellgetriebenen Entwicklung klinischer Entscheidungsunterstützungssysteme

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Abstract:

Einleitung: Systeme auf Basis von Algorithmen mit \glqqkünstlicher Intelligenz\grqq werden im Gesundheitswesen zunehmend praktisch eingesetzt. Durch die Medizininformatik-Initiative sollen zukünftig Daten aus Krankenversorgung und Forschung besser zugänglich werden. In diesem Rahmen[zum vollständigen Text gelangen Sie über die oben angegebene URL]

DOI: 10.3205/19gmds183

Projects: SMITH - Smart Medical Information Technology for Healthcare

Publication type: InProceedings

Journal: 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Publisher: German Medical Science GMS Publishing House

Human Diseases: No Human Disease specified

Citation:

Date Published: 8th Sep 2019

URL: https://www.smith.care/wp-content/uploads/2019/09/Poster_Phan-Vogtmann_GMDS_2019.pdf

Registered Mode: imported from a bibtex file

Authors: Lo Phan-Vogtmann an , Henner M. Kruse, Alexander Helhorn, Andrew J. Heidel, Eric Thomas, Kutaiba Saleh, André Scherag, Danny Ammon

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Phan-Vogtmann, L. A., Kruse, H. M., Helhorn, A., Heidel, A. J., Thomas, E., Saleh, K., Scherag, A., & Ammon, D. (2019). Rückverfolgbarkeit für künstliche Intelligenz: Umsetzung einer Traceability-Strategie bei der modellgetriebenen Entwicklung klinischer Entscheidungsunterstützungssysteme. 64. Jahrestagung Der Deutschen Gesellschaft Für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). https://doi.org/10.3205/19GMDS183
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