TY  - JOUR
AU  - Ellmann, Stephan
AU  - Seyler, Lisa
AU  - Gillmann, Clarissa
AU  - Popp, Vanessa
AU  - Treutlein, Christoph
AU  - Bozec, Aline
AU  - Uder, Michael
AU  - Bäuerle, Tobias
TI  - Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.
JO  - JoVE journal
VL  - 162
SN  - 1940-087X
CY  - Cambridge, MA
PB  - JoVE
M1  - DKFZ-2020-01789
SP  - 61235
PY  - 2020
AB  - 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
LB  - PUB:(DE-HGF)16
C6  - pmid:32865533
DO  - DOI:10.3791/61235
UR  - https://inrepo02.dkfz.de/record/157752
ER  -