Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.
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ABSTRACT:
SUBMITTER: Yamamoto Y
PROVIDER: S-EPMC5404264 | biostudies-other | 2017 Apr
REPOSITORIES: biostudies-other
Publications
Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.
Yamamoto Yoichiro Y Saito Akira A Tateishi Ayako A Shimojo Hisashi H Kanno Hiroyuki H Tsuchiya Shinichi S Ito Ken-Ichi KI Cosatto Eric E Graf Hans Peter HP Moraleda Rodrigo R RR Eils Roland R Grabe Niels N
Scientific reports 20170425
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ducta ...[more]
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