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A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas

Crossref DOI link: https://doi.org/10.1186/s12864-018-5177-9

Published Online: 2018-11-27

Published Print: 2018-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Lin, Sangdi

Wang, Chen

Zarei, Shabnam

Bell, Debra A.

Kerr, Sarah E.

Runger, George C.

Kocher, Jean-Pierre A.
Funding

Funding for this research was provided by:

The Center for Individualized Medicine, Mayo Clinic

Mayo Clinic Ovarian SPORE (P50 CA136393)
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Article History

Received: 14 December 2017

Accepted: 16 October 2018

First Online: 27 November 2018

Ethics approval and consent to participate

: All cases provided informed consent for use of their tissues and data in research; all protocols were approved by the Mayo Clinic Institutional Review Board (IRB Number: 13-006515).

: Not applicable as there is no identifiable individual data.

: The authors declare that they have no competing interests.

: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.