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- W4292242835 abstract "Multiple sclerosis (MS) research has been changing significantly over the last 20 years. In this study we aimed to explore its temporal research trends by using the state-of-the-art transformer-based machine learning technique for natural language processing (NLP). From our results, it emerges clearly that, while topics such as EAE and genetics of MS have been the focus of attention since a long time, more recently there has been growing attention towards MS-related symptoms such as cognitive impairment, fatigue, walking impairment and falls risk, as they are now recognized as key determinants of a patient's quality of life." @default.
- W4292242835 created "2022-08-19" @default.
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- W4292242835 date "2022-12-01" @default.
- W4292242835 modified "2023-09-27" @default.
- W4292242835 title "Emerging trends in multiple sclerosis research" @default.
- W4292242835 cites W2174706414 @default.
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- W4292242835 doi "https://doi.org/10.1016/j.msard.2022.104124" @default.
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