A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation-Reference-Cited by-同舟云学术

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A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation

Published:2020-11 Issue:11 Volume:1866 Page:165916
ISSN:0925-4439
Container-title:Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
language:en
Short-container-title:Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease

Author:

He Bingsheng,Dai Chan,Lang Jidong,Bing Pingping,Tian Geng,Wang Bo,Yang Jialiang

Funder

Natural Science Foundation of Hunan Province

project to introduce intelligence from oversea experts to the Changsha City

Publisher

Elsevier BV

Subject

Molecular Biology,Molecular Medicine

Reference43 articles.

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2. Psychiatric manifestations, personality traits and health-related quality of life in cancer of unknown primary site;Hyphantis;Psycho-oncology,2013

3. Hybrid model integrating immunohistochemistry and expression profiling for the classification of carcinomas of unknown primary site;Centeno;J. Mol. Diagn.,2010

4. G. Huebner, L. Morawietz, A. Floore, R. Buettner, G. Folprecht, L. Stork-Sloots, M. Dietel, 503 POSTER Comparative analysis of microarray testing and immunohistochemistry in patients with carcinoma of unknown primary – CUP syndrome, 5 (2007) 90–91.

5. S. Janick, L.-M. Elodie, M. Marie-Christine, R. Philippe, I. Marius, Immunohistochemistry for diagnosis of metastatic carcinomas of unknown primary site, Cancers, 10 (2018) 108-.

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