نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری تخصصی، علم اطلاعات و دانش‌شناسی، گروه علوم ارتباطات و دانش‌شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

2 استاد، علم اطلاعات و دانش‌شناسی، گروه علوم ارتباطات و دانش‌شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

3 دانشیار، ریاضی کاربردی، گروه ریاضی کاربردی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران

4 دانشیار، علم اطلاعات و دانش‌شناسی، گروه علوم ارتباطات ودانش شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

هدف: با توجه به اهمیت و جایگاهی که حوزه غدد درون‌ریز در بخش سلامت دارد، تسهیل بازیابی اطلاعات در این حوزه می‌تواند بسیار مهم باشد. مطالعه حاضر با هدف مدل‌سازی موضوعی مقالات منتشر شده پژوهشگران ایرانی در حوزه غدد درون‌ریز و متابولیسم در پایگاه استنادی علوم انجام گرفت.روش بررسی: این تحقیق از نوع توصیفی بود و با روش متن‌کاوی انجام شد. چکیده مقالات با استفاده از کلید واژه‌های منتخب سرعنوان موضوعی پزشکی MeSH (Medical Subject Headings) از پایگاه استنادی علوم استخراج گردید. 5552 مقاله از سال 1977 تا سال 2019 بازیابی شد. سپس متن چکیده‌ها در نرم‌افزار MATLAB مورد تحلیل و بررسی قرار گرفت و دسته‌بندی شد.یافته‌ها: دسته‌های موضوعی متشکل از 20 واژه و در 48 دسته استخراج گردید. بیماری دیابت با 7145 بار تکرار، بیشتر از سایر موضوعات مورد توجه پژوهشگران ایرانی قرار گرفته ‌است. دسته موضوعی مربوط به بیماری‌های سندرم متابولیک با بیشترین تعداد مقالات (304 مقاله) و دسته موضوعی شماره 47 که مربوط به بیماری‌های نرمی استخوان بود، کمترین تعداد مقالات (51 مقاله) را به خود اختصاص داد.نتیجه‌گیری: پژوهشگران ایرانی به تحقیقاتی با موضوع سندرم متابولیک بیشتر و به موضوعاتی مانند نرمی استخوان کمتر پرداخته‌ بودند. مباحثی شامل Dwarfism، Parathyroid Diseases، Pituitary Diseases، Gonadal Disorders، Polyendocrinopathies و Autoimmune که در موضوعات حاصل از مدل‌سازی موضوعی وجود نداشت، بیانگر خلأ موجود در پژوهش‌های محققان ایرانی می‌باشد که بر لزوم توجه بیشتر بر این حوزه‌ها تأکید می‌شود.

کلیدواژه‌ها

عنوان مقاله [English]

Analyzing the Status of Endocrinology and Metabolic Research in Iran Using Text Mining Methods

نویسندگان [English]

  • Omolbanin Asadi-Ghadiklaei 1
  • Nadjla Hariri 2
  • Maryam Khademi 3
  • Fahimeh Babalhavaeji 4

1 PhD Student, Knowledge and Information Science, Department of Communication and Knowledge Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor, Knowledge and Information Science, Department of Communication and Knowledge Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

3 Associate Professor, Applied Mathematics, Department of Applied Mathematics, South Tehran Branch Islamic Azad University, Tehran, Iran

4 Associate Professor, Knowledge and Information Science, Department of Communication and Knowledge Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

چکیده [English]

Introduction: Due to the importance and status of the endocrine field in the health sector, facilitating information retrieval in this field seems to be important. This study endeavored to run topic modeling of articles published by Iranian researchers in the field of endocrinology and metabolism in the science citation database.Methods: This descriptive study was done by text mining method. In this study, abstracts of articles were extracted from the science citation database using selected keywords of Medical Subject Headings (MeSH). 5552 articles were retrieved from 1977 to 2019, then the text of abstracts was analyzed and categorized in MATLAB software.Results: Subject categories with 20 items were extracted in 48 categories. Diabetes with 7145 recurrences has been considered by Iranian researchers more than other topics. Subject category related to metabolic syndrome diseases had the highest number of articles (304 articles) and subject category No. 47 which was related to osteoporosis had the lowest number of articles (51 articles).Conclusion: Iranian researchers have done more research on metabolic syndrome and less research on osteoporosis. Topic categories including Dwarfism, Parathyroid Diseases, Pituitary Diseases, Gonadal Disorders, Polyendocrinopathies, and Autoimmune that did not exist in the topics resulting from topic modeling indicate a gap in the research of Iranian researchers, that emphasizes the need for more attention to these areas.

کلیدواژه‌ها [English]

  • Topic Modeling
  • Endocrinology
  • Metabolism
  • Text Mining
  • Latent Dirichlet Allocation
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