Cargando…
Breast cancer outcome prediction with tumour tissue images and machine learning
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input. METHODS: Utilising tissue microarray (TMA) samples...
Autores principales: | Turkki, Riku, Byckhov, Dmitrii, Lundin, Mikael, Isola, Jorma, Nordling, Stig, Kovanen, Panu E., Verrill, Clare, von Smitten, Karl, Joensuu, Heikki, Lundin, Johan, Linder, Nina |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647903/ https://www.ncbi.nlm.nih.gov/pubmed/31119567 http://dx.doi.org/10.1007/s10549-019-05281-1 |
Ejemplares similares
-
Deep learning based tissue analysis predicts outcome in colorectal cancer
por: Bychkov, Dmitrii, et al.
Publicado: (2018) -
Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy
por: Bychkov, Dmitrii, et al.
Publicado: (2021) -
Outcome and biomarker supervised deep learning for survival prediction in two multicenter breast cancer series
por: Bychkov, Dmitrii, et al.
Publicado: (2022) -
Quantification of Estrogen Receptor-Alpha Expression in Human Breast Carcinomas With a Miniaturized, Low-Cost Digital Microscope: A Comparison with a High-End Whole Slide-Scanner
por: Holmström, Oscar, et al.
Publicado: (2015) -
Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples
por: Turkki, Riku, et al.
Publicado: (2016)