Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis

Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis

BackgroundStrategies to improve the selection of appropriate target journals may reduce delays in disseminating research results. Machine learning is increasingly used in content-based recommender algorithms to guide journal submissions for academic articles. Obje...

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Bibliographic Details
Main Authors: Carmelo Macri, Stephen Bacchi, Sheng Chieh Teoh, Wan Yin Lim, Lydia Lam, Sandy Patel, Mark Slee, Robert Casson, WengOnn Chan
Format: Article
Language:English
Published: JMIR Publications 2023-03-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2023/1/e42789

Internet

https://www.jmir.org/2023/1/e42789

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