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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主要な著者: 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
フォーマット: Artigo
言語:Russo
出版事項: IRBIS LLC 2020-08-01
シリーズ:Фармакоэкономика
主題:
big data analysis
pharmacoinformatics
artificial intelligence
evidence-based medicine
machine learning
publication quality assessment algorithms
thematic modeling
オンライン･アクセス:https://www.pharmacoeconomics.ru/jour/article/view/387
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