A CBR framework with gradient boosting based feature selection for lung cancer subtype classification-Reference-Cited by-同舟云学术

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A CBR framework with gradient boosting based feature selection for lung cancer subtype classification

Published:2017-07 Issue: Volume:86 Page:98-106
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Ramos-González Juan,López-Sánchez Daniel,Castellanos-Garzón Jose A.,de Paz Juan F.,Corchado Juan M.

Funder

Ministry of Education, Culture and Sports of the Spanish Government

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference51 articles.

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2. Current concepts on the molecular pathology of non-small cell lung carcinoma;Fujimoto,2014

3. Targeted therapy for non-small cell lung cancer: current standards and the promise of the future;Chan;Transl. Lung cancer Res.,2014

4. Non-small cell lung carcinoma: an overview on targeted therapy;Nascimento;Curr. drug targets,2015

5. Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma;Zhan;J. Thorac. Dis.,2015

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