Abstract
Artificial intelligence will undoubtedly shape technological developments in the next years – affecting biobanks as well. First concepts already exist for the possible application of AI in biobank processes. Data quality, which depends on sample quality, plays the decisive role here. For this reason, high and also overarching quality standards are important to prepare biobanks for these technological innovations. In addition, the requirements for sample and data quality will be significantly affected by the EU regulation for in vitro diagnostics as its transition period ends in 2022. The demand for human biospecimens will consequently rise.
In order to meet such requirements, the German Biobank Node (GBN) and the German Biobank Alliance (GBA) have established a quality management programme for German biobanks which includes e.g. an extensive quality manual and so-called “friendly” (cross-biobank) audits. The following article describes these developments with regard to their relevance for future biobank workflows using AI methods.
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Hartfeldt, C. et al. (2020). Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks. In: Holzinger, A., Goebel, R., Mengel, M., Müller, H. (eds) Artificial Intelligence and Machine Learning for Digital Pathology. Lecture Notes in Computer Science(), vol 12090. Springer, Cham. https://doi.org/10.1007/978-3-030-50402-1_5
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DOI: https://doi.org/10.1007/978-3-030-50402-1_5
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