Francesco Marchetti, Fabio De Martino, Marie Shamseddin, Stefano De Marchi, Cathrin Brisken. Variably Scaled Kernels Improve Classification of Hormonally-Treated Patient-Derived Xenografts. In 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020, Bari, Italy, May 27-29, 2020. pages 1-6, IEEE, 2020. [doi]
@inproceedings{MarchettiMSMB20,
title = {Variably Scaled Kernels Improve Classification of Hormonally-Treated Patient-Derived Xenografts},
author = {Francesco Marchetti and Fabio De Martino and Marie Shamseddin and Stefano De Marchi and Cathrin Brisken},
year = {2020},
doi = {10.1109/EAIS48028.2020.9122767},
url = {https://doi.org/10.1109/EAIS48028.2020.9122767},
researchr = {https://researchr.org/publication/MarchettiMSMB20},
cites = {0},
citedby = {0},
pages = {1-6},
booktitle = {2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020, Bari, Italy, May 27-29, 2020},
publisher = {IEEE},
isbn = {978-1-7281-4384-2},
}