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

Aleksandra Nabożny; Bartłomiej Balcerzak; Adam Wierzbicki; Mikołaj Morzy; Małgorzata Chlabicz

doi:10.2196/26065

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Title

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

Authors

Aleksandra Nabożny
Bartłomiej Balcerzak
Adam Wierzbicki
Mikołaj Morzy (WIiT) ^{[ 1 ][ 2.3 ][ P ]}
Małgorzata Chlabicz

^{[ 1 ]} Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2021

Published in

JMIR Medical Informatics

Journal year: 2021 | Journal volume: vol. 9 | Journal number: no. 11

Article type

scientific article

Publication language

english

Keywords

EN

active annotation
credibility
web-based medical information
fake news

Date of online publication

26.11.2021

Pages (from - to)

e26065-1 - e26065-19

DOI

10.2196/26065

URL

https://medinform.jmir.org/2021/11/e26065

Comments

Article Number: e26065

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

70

Ministry points / journal in years 2017-2021

70

Impact Factor

3,228

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