Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: approaches to the generalizations of accumulated data and the phenomenon of “fake news

Introduction. The English-language databases PubMed/MEDLINE and Embase are valuable information resources for finding original publications in basic and clinical medicine. Currently, there are no artificial intelligence systems to evaluate the quality of these publications.Aim. Development and testi...

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Détails bibliographiques
Auteurs principaux: I. Yu. Torshin, O. A. Gromova, L. V. Stakhovskaya, N. P. Vanchakova, A. N. Galustyan, Zh. D. Kobalava, T. R. Grishina, A. N. Gromov, I. A. Ilovaiskaya, V. M. Kodentsova, A. G. Kalacheva, O. A. Limanova, V. A. Maksimov, S. I. Malyavskaya, E. V. Mozgovaya, N. I. Tapilskaya, K. V. Rudakov, V. A. Semenov
Format: Artigo
Langue:Russo
Publié: IRBIS LLC 2020-08-01
Collection:Фармакоэкономика
Sujets:
big data analysis
pharmacoinformatics
artificial intelligence
evidence-based medicine
machine learning
publication quality assessment algorithms
thematic modeling
Accès en ligne:https://www.pharmacoeconomics.ru/jour/article/view/387
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