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A comprehensive overview of psoriatic research over the past 20 years: machine learning-based bibliometric analysis

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机构: [1]Sichuan Univ, West China Hosp, Dept Dermatol, Chengdu, Peoples R China [2]Sichuan Univ, West China Hosp, Clin Inst Inflammat & Immunol, Frontiers Sci Ctr Dis Related Mol Network,Lab Derm, Chengdu, Peoples R China [3]Univ Elect Sci & Technol China, Sichuan Canc Hosp & Inst, Dept Thoracic Surg, Sichuan Canc Ctr,Sch Med, Chengdu, Sichuan, Peoples R China
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关键词: psoriasis bibliometric machine learning natural language processing (NLP) latent Dirichlet allocation (LDA) algorithm

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Background The surge in the number of publications on psoriasis has posed significant challenges for researchers in effectively managing the vast amount of information. However, due to the lack of tools to process metadata, no comprehensive bibliometric analysis has been conducted.Objectives This study is to evaluate the trends and current hotspots of psoriatic research from a macroscopic perspective through a bibliometric analysis assisted by machine learning based semantic analysis.Methods Publications indexed under the Medical Subject Headings (MeSH) term "Psoriasis" from 2003 to 2022 were extracted from PubMed. The generative statistical algorithm latent Dirichlet allocation (LDA) was applied to identify specific topics and trends based on abstracts. The unsupervised Louvain algorithm was used to establish a network identifying relationships between topics.Results A total of 28,178 publications were identified. The publications were derived from 176 countries, with United States, China, and Italy being the top three countries. For the term "psoriasis", 9,183 MeSH terms appeared 337,545 times. Among them, MeSH term "Severity of illness index", "Treatment outcome", "Dermatologic agents" occur most frequently. A total of 21,928 publications were included in LDA algorithm, which identified three main areas and 50 branched topics, with "Molecular pathogenesis", "Clinical trials", and "Skin inflammation" being the most increased topics. LDA networks identified "Skin inflammation" was tightly associated with "Molecular pathogenesis" and "Biological agents". "Nail psoriasis" and "Epidemiological study" have presented as new research hotspots, and attention on topics of comorbidities, including "Cardiovascular comorbidities", "Psoriatic arthritis", "Obesity" and "Psychological disorders" have increased gradually.Conclusions Research on psoriasis is flourishing, with molecular pathogenesis, skin inflammation, and clinical trials being the current hotspots. The strong association between skin inflammation and biologic agents indicated the effective translation between basic research and clinical application in psoriasis. Besides, nail psoriasis, epidemiological study and comorbidities of psoriasis also draw increased attention.

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出版当年[2023]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
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出版当年[2023]版:
Q1 IMMUNOLOGY
最新[2023]版:
Q1 IMMUNOLOGY

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第一作者机构: [1]Sichuan Univ, West China Hosp, Dept Dermatol, Chengdu, Peoples R China [2]Sichuan Univ, West China Hosp, Clin Inst Inflammat & Immunol, Frontiers Sci Ctr Dis Related Mol Network,Lab Derm, Chengdu, Peoples R China
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通讯机构: [1]Sichuan Univ, West China Hosp, Dept Dermatol, Chengdu, Peoples R China [2]Sichuan Univ, West China Hosp, Clin Inst Inflammat & Immunol, Frontiers Sci Ctr Dis Related Mol Network,Lab Derm, Chengdu, Peoples R China
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