Model and Materials of ''Improved Accuracy in Colorectal Cancer Tissue Decomposition through Refinement of Established Deep Learning Solutions''

Name: Model and Materials of ''Improved Accuracy in Colorectal Cancer Tissue Decomposition through Refinement of Established Deep Learning Solutions''
Creator: Fabi Prezja
Published: 2023-09-19T10:15:45.118Z
Keywords: Machine Learning, Histopathology, Colorectal Cancer

Prezja, Fabi; Äyrämö, Sami; Pölönen, Ilkka; Ojala, Timo; Lahtinen, Suvi; Ruusuvuori, Pekka; Kuopio, Teijo

doi:10.17632/8wz5dttyyz.1

Model and Materials of ''Improved Accuracy in Colorectal Cancer Tissue Decomposition through Refinement of Established Deep Learning Solutions''

Published: 19 September 2023| Version 1 | DOI: 10.17632/8wz5dttyyz.1

Contributors:

, Sami Äyrämö, Ilkka Pölönen, Timo Ojala, Suvi Lahtinen, Pekka Ruusuvuori, Teijo Kuopio

Description

This dataset contains the highest performing trained model definition, weights, and additional materials from the Nature SR study titled ''Improved Accuracy in Colorectal Cancer Tissue Decomposition through Refinement of Established Deep Learning Solutions''. Please refer to the associated article for further details.

Model and Materials of ''Improved Accuracy in Colorectal Cancer Tissue Decomposition through Refinement of Established Deep Learning Solutions''

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