Narcolepsy: a machine learning bibliometric analysis (1996–2024)
Minheng Zhang, Xiaodong Hu, Haiyan Wu, Haixia Fan

TL;DR
This paper uses machine learning and bibliometric analysis to study global research trends in narcolepsy from 1996 to 2024.
Contribution
The study provides a comprehensive bibliometric analysis of narcolepsy research, highlighting trends in treatment and comorbidities.
Findings
The USA led in narcolepsy research publications, with Stanford University and other institutions as top contributors.
Recent research trends include medications like Pitolisant and comorbidities like obstructive sleep apnea.
Gaps remain in understanding neurotransmitter interactions and drug therapy efficacy in narcolepsy.
Abstract
Narcolepsy is a rare neurological cause of chronic sleepiness. This study aimed to better understand global narcolepsy through bibliometric analysis. Articles and reviews on narcolepsy were sourced from the Web of Science Core Collection. A bibliometric analysis was performed using Microsoft Excel, Python, CiteSpace, VOSviewer, R (bibliometrix), and the Online Analysis Platform of Literature Metrology to assess publication outputs, countries, institutions, authors, journals, co-cited references, and keywords. The analysis included 5,215 publications, with citations significantly increasing from 1996 to 2024. The USA led in publications, while the top institutions were Stanford University, INSERM, and Université de Montpellier. Key authors like Professors Plazzi G, Mignot E, and Dauvilliers Y greatly contributed to the field through numerous publications and high citation rates. Sleep…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsSleep and Wakefulness Research · Sleep and related disorders · EEG and Brain-Computer Interfaces
