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Feasibility of machine learning-based modeling and predicti..:

Shuang-Nan Zhou (14194625) ; Da-Wei Jv (14307275) ; Xiang-Fei Meng (523855)...
https://figshare.com/articles/dataset/Feasibility_of_machine_learning-based_modeling_and_prediction_using_multiple_centers_data_to_assess_intrahepatic_cholangiocarcinoma_outcomes/21786980. , 2022

Link: https://doi.org/10.6084/m9.figshare.21786980.v1

RT Journal
T1 <Title>Feasibility of machine learning-based modeling and prediction using multiple centers data to assess intrahepatic cholangiocarcinoma outcomes</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftunivfreestate:oai:figshare.com:article_21786980&Exemplar=1&LAN=DE
				
A1 Shuang-Nan Zhou (14194625)
A1 Da-Wei Jv (14307275)
A1 Xiang-Fei Meng (523855)
A1 Jing-Jing Zhang (182712)
A1 Chun Liu (47227)
A1 Ze-Yi Wu (14307278)
A1 Na Hong (638630)
A1 Yin-Ying Lu (345111)
A1 Ning Zhang (23771)
YR 2022
K1 Medicine
K1 Genetics
K1 Biotechnology
K1 Immunology
K1 Cancer
K1 Biological Sciences not elsewhere classified
K1 Mathematical Sciences not elsewhere classified
K1 Chemical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 Intrahepatic cholangiocarcinoma
K1 machine-learning
K1 prognostic system
K1 clinical decision
JF https://figshare.com/articles/dataset/Feasibility_of_machine_learning-based_modeling_and_prediction_using_multiple_centers_data_to_assess_intrahepatic_cholangiocarcinoma_outcomes/21786980
LK http://dx.doi.org/https://doi.org/10.6084/m9.figshare.21786980.v1
DO https://doi.org/10.6084/m9.figshare.21786980.v1
SF ELIB - SuUB Bremen

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