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Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms

Crossref DOI link: https://doi.org/10.1186/s12918-019-0693-z

Published Online: 2019-04-05

Published Print: 2019-04

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

Authors

Hao, Yangyang

Duh, Quan-Yang

Kloos, Richard T.

Babiarz, Joshua

Harrell, R. Mack

Traweek, S. Thomas

Kim, Su Yeon

Fedorowicz, Grazyna

Walsh, P. Sean

Sadow, Peter M.

Huang, Jing

Kennedy, Giulia C.
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Article History

First Online: 5 April 2019

Ethics approval and consent to participate

: Ethics approval was obtained prior to the initiation of the studies described in this manuscript. Study samples were collected according to protocols that were reviewed and approved by study site institutional review boards (IRB) or central IRBs (Liberty IRB, DeLand, Florida; now Chesapeake IRB, and Copernicus Group Independent Review Board, Cary, North Carolina).

: Not applicable.

: YH, RTK, JB, SYK, GF, PSW, JH, and GCK are employed by Veracyte, Inc.

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