A pathologist-annotated dataset for validating artificial intelligence: A project description and pilot study

A pathologist-annotated dataset for validating artificial intelligence: A project description and pilot study

Purpose: Validating artificial intelligence algorithms for clinical use in medical images is a challenging endeavor due to a lack of standard reference data (ground truth). This topic typically occupies a small portion of the discussion in research papers since most of the efforts are focused on dev...

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Bibliographic Details
Main Authors: Sarah N Dudgeon, Si Wen, Matthew G Hanna, Rajarsi Gupta, Mohamed Amgad, Manasi Sheth, Hetal Marble, Richard Huang, Markus D Herrmann, Clifford H Szu, Darick Tong, Bruce Werness, Evan Szu, Denis Larsimont, Anant Madabhushi, Evangelos Hytopoulos, Weijie Chen, Rajendra Singh, Steven N Hart, Ashish Sharma, Joel Saltz, Roberto Salgado, Brandon D Gallas
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Journal of Pathology Informatics
Subjects:
artificial intelligence validation
medical image analysis
pathology
reference standard
tumor-infiltrating lymphocytes
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2021;volume=12;issue=1;spage=45;epage=45;aulast=Dudgeon

Internet

http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2021;volume=12;issue=1;spage=45;epage=45;aulast=Dudgeon

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