Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies

Haegele M, Mueller KR, Denkert C, Schneeweiss A, Sinn BV, Untch M, Van Mackelenbergh MT, Jackisch C, Nekljudova V, Karn T, Alber M, Marme F, Schem C, Stickeler E, Fasching P, Mueller V, Weber KE, Lederer B, Loibl S, Klauschen F (2022)


Publication Type: Conference contribution

Publication year: 2022

Journal

Publisher: ELSEVIER

City/Town: AMSTERDAM

Pages Range: S572-S573

Conference Proceedings Title: ANNALS OF ONCOLOGY

DOI: 10.1016/j.annonc.2022.07.101

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How to cite

APA:

Haegele, M., Mueller, K.-R., Denkert, C., Schneeweiss, A., Sinn, B.V., Untch, M.,... Klauschen, F. (2022). Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies. In ANNALS OF ONCOLOGY (pp. S572-S573). AMSTERDAM: ELSEVIER.

MLA:

Haegele, M., et al. "Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies." Proceedings of the Annual Meeting of the European-Society-for-Medical-Oncology (ESMO) AMSTERDAM: ELSEVIER, 2022. S572-S573.

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