%0 Journal Article
%A Ellmann, Stephan
%A Seyler, Lisa
%A Gillmann, Clarissa
%A Popp, Vanessa
%A Treutlein, Christoph
%A Bozec, Aline
%A Uder, Michael
%A Bäuerle, Tobias
%T Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.
%J JoVE journal
%V 162
%@ 1940-087X
%C Cambridge, MA
%I JoVE
%M DKFZ-2020-01789
%P 61235
%D 2020
%X Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy exceeding its constituents. This protocol describes the development of an ML algorithm to predict the growth of breast cancer bone macrometastases in a rat model before any abnormalities are observable with standard imaging methods. Such an algorithm can facilitate the detection of early metastatic disease (i.e., micrometastasis) that is regularly missed during staging examinations. The applied metastasis model is site-specific, meaning that the rats develop metastases exclusively in their right hind leg. The model's tumor-take rate is 60
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:32865533
%R 10.3791/61235
%U https://inrepo02.dkfz.de/record/157752