Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification

Affiliations

¹ Centre for Medical Imaging, University College London, London, UK. Electronic address: s.halligan@ucl.ac.uk.
² Centre for Medical Imaging, University College London, London, UK.

Comment

S Halligan et al. Clin Radiol. 2019 Feb.

. 2019 Feb;74(2):161.

doi: 10.1016/j.crad.2018.11.010. Epub 2018 Dec 15.

¹ Centre for Medical Imaging, University College London, London, UK. Electronic address: s.halligan@ucl.ac.uk.
² Centre for Medical Imaging, University College London, London, UK.

No abstract available

Comment in

Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification. A reply.
Yates EJ, Yates LC, Harvey H. Yates EJ, et al. Clin Radiol. 2019 Feb;74(2):162. doi: 10.1016/j.crad.2018.11.008. Epub 2018 Dec 15. Clin Radiol. 2019. PMID: 30563698 No abstract available.
Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification. Editor's reply.
Weston M. Weston M. Clin Radiol. 2019 Feb;74(2):163. doi: 10.1016/j.crad.2018.12.001. Epub 2018 Dec 24. Clin Radiol. 2019. PMID: 30591212 No abstract available.

Machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification.
Yates EJ, Yates LC, Harvey H. Yates EJ, et al. Clin Radiol. 2018 Sep;73(9):827-831. doi: 10.1016/j.crad.2018.05.015. Epub 2018 Jun 10. Clin Radiol. 2018. PMID: 29898829