Detection of invasive lobular carcinoma using an artificial intelligence algorithm based on genetic ground truth Meeting Abstract

  

Authors:	Pareja, F.; Dopeso, H.; Wang, Y.; Goldfinger, M.; Gazzo, A.; Derakhshan, F.; da Silva, E. M.; Selenica, P.; Basili, T.; Danielle, S.; Brown, D.; Sue, J.; Ye, Q.; Da Cruz Paula, A.; Banerjee, M.; Lee, M.; Godrich, R.; Casson, A.; Weigelt, B.; Wen, H.; Brogi, E.; Hanna, M.; Kunz, J.; Kanan, C.; Klimstra, D.; Fuchs, T.; Reis-Filho, J.
Abstract Title:	Detection of invasive lobular carcinoma using an artificial intelligence algorithm based on genetic ground truth
Meeting Title:	112th Annual Meeting of the United States & Canadian Academy of Pathology (USCAP): Facing the Unknown
Journal Title:	Laboratory Investigation
Volume:	103
Issue:	3 Suppl.
Meeting Dates:	2023 Mar 11-16
Meeting Location:	New Orleans, LA
ISSN:	0023-6837
Publisher:	Nature Publishing Group
Date Published:	2023-03-01
Start Page:	S194
Language:	English
ACCESSION:	WOS:000990969800206
PROVIDER:	wos
DOI:	10.1016/j.labinv.2023.100081
Notes:	Meeting Abstract: 205, in the section "Breast Pathology" -- MSK authors Danielle Share's first and last names are reversed on the original publication -- Source: Wos

https://synapse.mskcc.org/synapse/works/has_related_data_chk/207808