Deep learning-based classification of mesothelioma improves prediction of patient outcome-Reference-Cited by-同舟云学术

Deep learning-based classification of mesothelioma improves prediction of patient outcome

Published:2019-10 Issue:10 Volume:25 Page:1519-1525
ISSN:1078-8956
Container-title:Nature Medicine
language:en
Short-container-title:Nat Med

Author:

Courtiol Pierre,Maussion Charles,Moarii Matahi,Pronier Elodie,Pilcer Samuel,Sefta Meriem,Manceron Pierre,Toldo Sylvain,Zaslavskiy Mikhail,Le Stang Nolwenn^ORCID,Girard Nicolas,Elemento Olivier,Nicholson Andrew G.,Blay Jean-Yves^ORCID,Galateau-Sallé Françoise,Wainrib Gilles,Clozel Thomas^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

Link

http://www.nature.com/articles/s41591-019-0583-3.pdf

Reference38 articles.

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2. Galateau-Sallé, F. et al. New insights on diagnostic reproducibility of biphasic mesotheliomas: a multi-institutional evaluation by the International Mesothelioma Panel from the MESOPATH reference center. J. Thorac. Oncol. 13, 1189–1203 (2018).

3. Noonan, C. W. Environmental asbestos exposure and mesothelioma. Ann. Transl. Med. 5, 234 (2017).

4. Lacourt, A. et al. Dose–time-response association between occupational asbestos exposure and pleural mesothelioma. Occup. Environ. Med. 74, 691–697 (2017).

5. Robinson, B. W. S. & Lake, R. A. Advances in malignant mesothelioma. N. Engl. J. Med. 353, 1591–1603 (2005).

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