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ISSN:
2291-9694
Disciplines
(Field of Science):
- information and communication technology (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- medical biology (Medical and Health Sciences )
- medical sciences (Medical and Health Sciences )
- health sciences (Medical and Health Sciences )
- biotechnology (Natural sciences)
- computer and information sciences (Natural sciences)
(Field of Science)
Ministry points: Help
| Year | Points | List |
|---|---|---|
| Year 2024 | 70 | Ministry scored journals list 2024 |
| Year | Points | List |
|---|---|---|
| 2024 | 70 | Ministry scored journals list 2024 |
| 2023 | 70 | Ministry Scored Journals List |
| 2022 | 70 | Ministry Scored Journals List 2019-2022 |
| 2021 | 70 | Ministry Scored Journals List 2019-2022 |
| 2020 | 70 | Ministry Scored Journals List 2019-2022 |
| 2019 | 70 | Ministry Scored Journals List 2019-2022 |
Model:
Open Access
Points CiteScore:
| Year | Points |
|---|---|
| Year 2023 | 7.9 |
| Year | Points |
|---|---|
| 2023 | 7.9 |
| 2022 | 5.6 |
| 2021 | 3.8 |
| 2020 | 2.9 |
Impact Factor:
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Sherpa Romeo:
Papers published in journal
Filters
total: 1
Catalog Journals
Year 2021
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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