- |
-
Machine learning techniques during the COVID-19 pandemic: A Bibliometric Analysis
Poster Presentation
Authors
1Information Technology dept., Tarbiat Modares University, Tehran, Iran
2Information Technology department, Tarbiat Modares University, Tehran, Iran
Abstract
The Coronavirus pandemic (COVID-19) has
encouraged researchers to produce significant scientific
research in this field in reputable international citation
databases. In this regard, the regular identification and
evaluation of scientific outputs to know the current situation is
highly prioritized. One of the methods of evaluating scientific
research activities is scientometric, which has many
applications in describing, explaining and predicting the
scientific status of researchers and research centers in various
national and international fields and provides efficient methods
for monitoring and ranking organizations, researchers,
journals and countries. On the other hand, in recent years, the
use of various scientometric techniques, including co-word
analysis, co-authorship network and scientific network, has
been a great help in discovering the direction of researchers'
production in a field of science and its hidden and overt
dimensions. One of the most popular areas since the start of
the COVID-19 epidemic has been research the use of artificial
intelligence and especially machine learning techniques in the
prediction, diagnosis and treatment of this disease. In this
research, 2659 articles indexed in this field in the PubMed
citation database from the beginning of the COVID-19
epidemic until now have been reviewed. The findings of this
research show that America, China, India and England are the
countries that have cooperated the most with other countries.
Also, the results of this research showed that deep learning and
CNN had been significantly used in researchers' studies.
encouraged researchers to produce significant scientific
research in this field in reputable international citation
databases. In this regard, the regular identification and
evaluation of scientific outputs to know the current situation is
highly prioritized. One of the methods of evaluating scientific
research activities is scientometric, which has many
applications in describing, explaining and predicting the
scientific status of researchers and research centers in various
national and international fields and provides efficient methods
for monitoring and ranking organizations, researchers,
journals and countries. On the other hand, in recent years, the
use of various scientometric techniques, including co-word
analysis, co-authorship network and scientific network, has
been a great help in discovering the direction of researchers'
production in a field of science and its hidden and overt
dimensions. One of the most popular areas since the start of
the COVID-19 epidemic has been research the use of artificial
intelligence and especially machine learning techniques in the
prediction, diagnosis and treatment of this disease. In this
research, 2659 articles indexed in this field in the PubMed
citation database from the beginning of the COVID-19
epidemic until now have been reviewed. The findings of this
research show that America, China, India and England are the
countries that have cooperated the most with other countries.
Also, the results of this research showed that deep learning and
CNN had been significantly used in researchers' studies.
Keywords
Proceeding Title [Persian]
Machine learning techniques during the COVID-19 pandemic: A Bibliometric Analysis
Authors [Persian]
Abstract [Persian]
The Coronavirus pandemic (COVID-19) has
encouraged researchers to produce significant scientific
research in this field in reputable international citation
databases. In this regard, the regular identification and
evaluation of scientific outputs to know the current situation is
highly prioritized. One of the methods of evaluating scientific
research activities is scientometric, which has many
applications in describing, explaining and predicting the
scientific status of researchers and research centers in various
national and international fields and provides efficient methods
for monitoring and ranking organizations, researchers,
journals and countries. On the other hand, in recent years, the
use of various scientometric techniques, including co-word
analysis, co-authorship network and scientific network, has
been a great help in discovering the direction of researchers'
production in a field of science and its hidden and overt
dimensions. One of the most popular areas since the start of
the COVID-19 epidemic has been research the use of artificial
intelligence and especially machine learning techniques in the
prediction, diagnosis and treatment of this disease. In this
research, 2659 articles indexed in this field in the PubMed
citation database from the beginning of the COVID-19
epidemic until now have been reviewed. The findings of this
research show that America, China, India and England are the
countries that have cooperated the most with other countries.
Also, the results of this research showed that deep learning and
CNN had been significantly used in researchers' studies.
encouraged researchers to produce significant scientific
research in this field in reputable international citation
databases. In this regard, the regular identification and
evaluation of scientific outputs to know the current situation is
highly prioritized. One of the methods of evaluating scientific
research activities is scientometric, which has many
applications in describing, explaining and predicting the
scientific status of researchers and research centers in various
national and international fields and provides efficient methods
for monitoring and ranking organizations, researchers,
journals and countries. On the other hand, in recent years, the
use of various scientometric techniques, including co-word
analysis, co-authorship network and scientific network, has
been a great help in discovering the direction of researchers'
production in a field of science and its hidden and overt
dimensions. One of the most popular areas since the start of
the COVID-19 epidemic has been research the use of artificial
intelligence and especially machine learning techniques in the
prediction, diagnosis and treatment of this disease. In this
research, 2659 articles indexed in this field in the PubMed
citation database from the beginning of the COVID-19
epidemic until now have been reviewed. The findings of this
research show that America, China, India and England are the
countries that have cooperated the most with other countries.
Also, the results of this research showed that deep learning and
CNN had been significantly used in researchers' studies.
Keywords [Persian]
COVID-19، machine learning techniques، bibliometric analysis، co-word analysis