Deep learning based tissue analysis predicts outcome in colorectal cancer

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue sam...

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Bibliographic Details
Published in:	Scientific reports Vol. 8; no. 1; pp. 3395 - 11
Main Authors:	Bychkov, Dmitrii, Linder, Nina, Turkki, Riku, Nordling, Stig, Kovanen, Panu E., Verrill, Clare, Walliander, Margarita, Lundin, Mikael, Haglund, Caj, Lundin, Johan
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 21.02.2018 Nature Publishing Group
Subjects:	631/114/1305 692/4028/67/1504/1885 Aged Algorithms Classification Colorectal cancer Colorectal carcinoma Colorectal Neoplasms - pathology Deep Learning Eosine Yellowish-(YS) - administration & dosage Female Hematoxylin - administration & dosage Humanities and Social Sciences Humans Image Processing, Computer-Assisted - methods Information processing Learning algorithms Machine Learning Male Middle Aged multidisciplinary Prognosis Retrospective Studies Risk groups Science Science (multidisciplinary) Tissue analysis Tumors
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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