<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName> Iranian Association for Intelligence and Talent Studies</PublisherName>
      <JournalTitle>International Journal of Education and Cognitive Sciences</JournalTitle>
      <Issn>3041-8828</Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2022</Year>
        <Month>06</Month>
        <Day>21</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Investigating the impact of artificial intelligence technology in medical electronics education</ArticleTitle>
    <VernacularTitle>--</VernacularTitle>
    <FirstPage></FirstPage>
    <LastPage></LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>-</FirstName>
        <LastName>-</LastName>
        <Affiliation>Master&amp;amp;#039;s degree in software engineering, Isfahan University, Isfahan, Iran</Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <Abstract>The purpose of this research is to identify and explain the capabilities of artificial intelligence in medical e-learning. To review and analyze the strengths and weaknesses, opportunities and threats, the opinions of 25 managers, professors, experts and experts in the field of artificial intelligence and professors in the field of medicine and health have been used. Among the selected people in this field, we can refer to people who have books, articles, authorships, translations in the field of medicine and artificial intelligence, and also have work experience as university professors, doctors, hospital heads, and consultants in terms of education and position. Opportunities, threats, strengths and weaknesses were collected from the community of experts based on an open questionnaire and interviews using the grand theory method. Then weighting and ranking has been done using the Shannon entropy technique. After ranking, 18 opportunities, 13 threats, 15 strengths and 14 weaknesses were identified. Then, using the strategic planning quantitative matrix, the indicators were scored and weighted. The total score of the internal factors was 2.469 and the total of the external factors was 2.316, which was drawn on the matrix, and Tehaji's strategy was chosen to formulate strategies for the use of artificial intelligence in the field of electronic medical education. Therefore, the strategy was presented with an aggressive approach.</Abstract>
    <OtherAbstract Language="FA">--</OtherAbstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">--</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Artificial intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">E-learning</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Medicine</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">health and health</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Patient</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journalecs.com/index.php/ecs/article/download/278/262</ArchiveCopySource>
  </Article>
</ArticleSet>
