Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images-Reference-Cited by-同舟云学术

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images

Published:2019-03-08 Issue:3 Volume:2 Page:e190442
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Nir Guy¹²,Karimi Davood¹,Goldenberg S. Larry²,Fazli Ladan²,Skinnider Brian F.³⁴,Tavassoli Peyman²⁵,Turbin Dmitry³,Villamil Carlos F.⁴,Wang Gang⁴,Thompson Darby J. S.⁶⁷,Black Peter C.²,Salcudean Septimiu E.¹²

Affiliation:

1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada

2. Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada

3. Department of Pathology and Laboratory Medicine, Vancouver General Hospital, Vancouver, British Columbia, Canada

4. British Columbia Cancer Agency, Vancouver, British Columbia, Canada

5. Richmond Hospital, Vancouver Coastal Health, Richmond, British Columbia, Canada

6. Emmes Canada, Burnaby, British Columbia, Canada

7. Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

http:///jamanetworkopen/article-pdf/2/3/e190442/17330456/nir_2019_oi_190035.pdf

Reference17 articles.

1. Digital images and the future of digital pathology.;Pantanowitz;J Pathol Inform,2010

2. Image analysis and machine learning in digital pathology: challenges and opportunities.;Madabhushi;Med Image Anal,2016

3. Interobserver reproducibility of Gleason grading of prostatic carcinoma: urologic pathologists.;Allsbrook;Hum Pathol,2001

4. Interobserver reproducibility of Gleason grading of prostatic carcinoma: general pathologist.;Allsbrook;Hum Pathol,2001

5. An audit of inter-observer variability in Gleason grading of prostate cancer biopsies: the experience of central pathology review in the North West of England.;Salmo;Integr Cancer Sci Ther,2015

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