Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Valerio Maggio"'
Autor:
Marco Chierici, Margherita Francescatto, Giuseppe Jurman, Nicole Bussola, Andrea Bizzego, Luca Cima, Marco Cristoforetti, Valerio Maggio, Cesare Furlanello
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 3, p e1006269 (2019)
Artificial Intelligence is exponentially increasing its impact on healthcare. As deep learning is mastering computer vision tasks, its application to digital pathology is natural, with the promise of aiding in routine reporting and standardizing resu
Publikováno v:
PLoS ONE, Vol 13, Iss 12, p e0208924 (2018)
PLoS ONE
PLoS ONE
We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e.g., a risk stratification schema to improve prognostic profiling. We present the first application
Autor:
Claudio Agostinelli, Diego Fioravanti, Ylenia Giarratano, Valerio Maggio, Cesare Furlanello, Giuseppe Jurman, Marco Chierici
Publikováno v:
BMC Bioinformatics
Fioravanti, D, Giarratano, Y, Maggio, V, Agostinelli, C, Chierici, M, Jurman, G & Furlanello, C 2018, ' Phylogenetic convolutional neural networks in metagenomics ', BMC Bioinformatics, vol. 19, no. Suppl 2, pp. 49 . https://doi.org/10.1186/s12859-018-2033-5
BMC Bioinformatics, Vol 19, Iss S2, Pp 1-13 (2018)
Fioravanti, D, Giarratano, Y, Maggio, V, Agostinelli, C, Chierici, M, Jurman, G & Furlanello, C 2018, ' Phylogenetic convolutional neural networks in metagenomics ', BMC Bioinformatics, vol. 19, no. Suppl 2, pp. 49 . https://doi.org/10.1186/s12859-018-2033-5
BMC Bioinformatics, Vol 19, Iss S2, Pp 1-13 (2018)
Background: Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architectu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73a94247be22db3eaba9742e481e6906
http://arxiv.org/abs/1709.02268
http://arxiv.org/abs/1709.02268