Published on in Vol 9 , No 11 (2021) :November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26065, first published .
Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning

Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning

Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning

Aleksandra Nabożny   1 , MSc ;   Bartłomiej Balcerzak   2 , PhD ;   Adam Wierzbicki   2 , Prof Dr Hab ;   Mikołaj Morzy   3 , PhD, DSc ;   Małgorzata Chlabicz   4 , MD, PhD

1 Department of Software Engineering, Gdańsk University of Technology, Gdańsk, PL

2 Polish-Japanese Academy of Information Technology, Warsaw, PL

3 Faculty of Computing and Telecommunications, Poznan University of Technology, Poznań, PL

4 Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Białystok, Białystok, PL

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