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Scientometric Study of Research in Information Retrieval in Medical Sciences

Background: Mapping scientific trends is one of the most important missions of scientometric research for effective research. The main goal of this paper was to visualize and draw the intellectual and cognitive structures of information retrieval (IR) in the medical sciences using science mapping. M...

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Autores principales: Mohammadi, Masoud, Roshandel, Gholamreza, Ghazimirsaeid, Seyed Javad, Zarinbal, Marzieh, Hosseini Beheshti, MolukoSadat, Sheikhshoaei, Fatemeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Iran University of Medical Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448488/
https://www.ncbi.nlm.nih.gov/pubmed/36128279
http://dx.doi.org/10.47176/mjiri.36.65
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author Mohammadi, Masoud
Roshandel, Gholamreza
Ghazimirsaeid, Seyed Javad
Zarinbal, Marzieh
Hosseini Beheshti, MolukoSadat
Sheikhshoaei, Fatemeh
author_facet Mohammadi, Masoud
Roshandel, Gholamreza
Ghazimirsaeid, Seyed Javad
Zarinbal, Marzieh
Hosseini Beheshti, MolukoSadat
Sheikhshoaei, Fatemeh
author_sort Mohammadi, Masoud
collection PubMed
description Background: Mapping scientific trends is one of the most important missions of scientometric research for effective research. The main goal of this paper was to visualize and draw the intellectual and cognitive structures of information retrieval (IR) in the medical sciences using science mapping. Methods: In this cross-sectional scientometric study, we recruited all documents indexed in the Web of Science database with the topic of storing and retrieval of information in medical sciences. To analyze the results, 3 software, SciMAT-v1.1.04, VOSviewer-v1.6.14, CitNetExplorer_v1.0.0, were used. Results: Our results showed that most scientific productions in this field fall into 2 categories: (1) effective methods of organizing information and (2) application and operation of the IR system in the process of intelligent questioning and answering, and analyzing information behaviors of physicians and health professionals. The results showed that the similarity index increased over time from 0.43 to 0.71. Analysis of the findings showed that similarity measures, expert systems, concepts, experience, answers, and multimodel IR clusters were considered as mature and completely centralized clusters in the first quarter of the strategic chart. Conclusion: Because of the dramatic approximation of the vocabulary used by researchers and a relative slowdown in the growth rate of the subject's domain in the last decade, it seems necessary to pay attention to the expansion of the fields of IR and the application of its concepts in medical information sciences. Also, it can be recommended that designers of IR systems and techniques in medical information sciences pay more attention to human factors attentively to develop new technologies and tools.
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spelling pubmed-94484882022-09-19 Scientometric Study of Research in Information Retrieval in Medical Sciences Mohammadi, Masoud Roshandel, Gholamreza Ghazimirsaeid, Seyed Javad Zarinbal, Marzieh Hosseini Beheshti, MolukoSadat Sheikhshoaei, Fatemeh Med J Islam Repub Iran Original Article Background: Mapping scientific trends is one of the most important missions of scientometric research for effective research. The main goal of this paper was to visualize and draw the intellectual and cognitive structures of information retrieval (IR) in the medical sciences using science mapping. Methods: In this cross-sectional scientometric study, we recruited all documents indexed in the Web of Science database with the topic of storing and retrieval of information in medical sciences. To analyze the results, 3 software, SciMAT-v1.1.04, VOSviewer-v1.6.14, CitNetExplorer_v1.0.0, were used. Results: Our results showed that most scientific productions in this field fall into 2 categories: (1) effective methods of organizing information and (2) application and operation of the IR system in the process of intelligent questioning and answering, and analyzing information behaviors of physicians and health professionals. The results showed that the similarity index increased over time from 0.43 to 0.71. Analysis of the findings showed that similarity measures, expert systems, concepts, experience, answers, and multimodel IR clusters were considered as mature and completely centralized clusters in the first quarter of the strategic chart. Conclusion: Because of the dramatic approximation of the vocabulary used by researchers and a relative slowdown in the growth rate of the subject's domain in the last decade, it seems necessary to pay attention to the expansion of the fields of IR and the application of its concepts in medical information sciences. Also, it can be recommended that designers of IR systems and techniques in medical information sciences pay more attention to human factors attentively to develop new technologies and tools. Iran University of Medical Sciences 2022-06-16 /pmc/articles/PMC9448488/ /pubmed/36128279 http://dx.doi.org/10.47176/mjiri.36.65 Text en © 2022 Iran University of Medical Sciences https://creativecommons.org/licenses/by-nc-sa/1.0/This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial-ShareAlike 1.0 License (CC BY-NC-SA 1.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.
spellingShingle Original Article
Mohammadi, Masoud
Roshandel, Gholamreza
Ghazimirsaeid, Seyed Javad
Zarinbal, Marzieh
Hosseini Beheshti, MolukoSadat
Sheikhshoaei, Fatemeh
Scientometric Study of Research in Information Retrieval in Medical Sciences
title Scientometric Study of Research in Information Retrieval in Medical Sciences
title_full Scientometric Study of Research in Information Retrieval in Medical Sciences
title_fullStr Scientometric Study of Research in Information Retrieval in Medical Sciences
title_full_unstemmed Scientometric Study of Research in Information Retrieval in Medical Sciences
title_short Scientometric Study of Research in Information Retrieval in Medical Sciences
title_sort scientometric study of research in information retrieval in medical sciences
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448488/
https://www.ncbi.nlm.nih.gov/pubmed/36128279
http://dx.doi.org/10.47176/mjiri.36.65
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