Literature DB >> 31092857

Author Correction: Automated Gleason grading of prostate cancer tissue microarrays via deep learning.

Eirini Arvaniti1,2, Kim S Fricker3, Michael Moret1, Niels Rupp3, Thomas Hermanns4, Christian Fankhauser4, Norbert Wey3, Peter J Wild3,5, Jan H Rüschoff6, Manfred Claassen7,8.   

Abstract

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Entities:  

Year:  2019        PMID: 31092857      PMCID: PMC6520401          DOI: 10.1038/s41598-019-43989-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Correction to: Scientific Reports 10.1038/s41598-018-30535-1, published online 13 August 2018 This Article contains an error in the Discussion section. “The low-risk and intermediate-risk groups defined by the model’s predictions were more significantly separated compared to the sfirst study where deep learning-based predictions are used for survival analysis in a prostate cancer cohort.” should read: “The low-risk and intermediate-risk groups defined by the model’s predictions were more significantly separated compared to the corresponding groups defined by either pathologist’s annotations. To our knowledge, this is the first study where deep learning-based predictions are used for survival analysis in a prostate cancer cohort.”
  1 in total

1.  Using deep learning to detect patients at risk for prostate cancer despite benign biopsies.

Authors:  Bojing Liu; Yinxi Wang; Philippe Weitz; Johan Lindberg; Johan Hartman; Wanzhong Wang; Lars Egevad; Henrik Grönberg; Martin Eklund; Mattias Rantalainen
Journal:  iScience       Date:  2022-06-23
  1 in total

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