ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.
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%0 Journal Article
%1 journals/bib/YaoLTLXJZLTTHLY22
%A Yao, Yuhua
%A Lv, Yaping
%A Tong, Ling
%A Liang, Yuebin
%A Xi, Shuxue
%A Ji, Binbin
%A Zhang, Guanglu
%A Li, Ling
%A Tian, Geng
%A Tang, Min
%A Hu, Xiyue
%A Li, Shijun
%A Yang, Jialiang
%D 2022
%J Briefings Bioinform.
%K dblp
%N 6
%T ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.
%U http://dblp.uni-trier.de/db/journals/bib/bib23.html#YaoLTLXJZLTTHLY22
%V 23
@article{journals/bib/YaoLTLXJZLTTHLY22,
added-at = {2022-12-25T00:00:00.000+0100},
author = {Yao, Yuhua and Lv, Yaping and Tong, Ling and Liang, Yuebin and Xi, Shuxue and Ji, Binbin and Zhang, Guanglu and Li, Ling and Tian, Geng and Tang, Min and Hu, Xiyue and Li, Shijun and Yang, Jialiang},
biburl = {https://www.bibsonomy.org/bibtex/2a4e8e807266fc4fb3c6fcb9711115282/dblp},
ee = {https://doi.org/10.1093/bib/bbac448},
interhash = {2d3e8c7c82690a49a6927358d8b1c79b},
intrahash = {a4e8e807266fc4fb3c6fcb9711115282},
journal = {Briefings Bioinform.},
keywords = {dblp},
number = 6,
timestamp = {2024-04-08T19:24:06.000+0200},
title = {ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.},
url = {http://dblp.uni-trier.de/db/journals/bib/bib23.html#YaoLTLXJZLTTHLY22},
volume = 23,
year = 2022
}
