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<article article-type="research-article" dtd-version="1.3" xml:lang="ru">
  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-title-group>
        <journal-title>Technoeconomics</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Technoeconomics</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2949-1290</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">3</article-id>
      <article-id pub-id-type="doi">10.57809/2024.3.4.11.3</article-id>
      <title-group>
        <article-title>Artificial intelligence and artificial neural networks in healthcare</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Искусственный интеллект и искусственные нейронные сети в сфере здравоохранения</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Ignatiev</surname>
            <given-names>Pavel</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-4822-6768</contrib-id>
          <contrib-id contrib-id-type="scopus">57210345222</contrib-id>
          <name>
            <surname>Levina</surname>
            <given-names>Anastasia</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St.Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2024-12-27">
        <day>27</day>
        <month>12</month>
        <year>2024</year>
      </pub-date>
      <volume>3</volume>
      <issue>4</issue>
      <issue-id pub-id-type="publisher-id">11</issue-id>
      <fpage>28</fpage>
      <lpage>41</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://technoeconomics.spbstu.ru/userfiles/files/Issues/11/3-Ignatiev-Levina.pdf"/>
      <abstract xml:lang="en">
        <p>The healthcare industry makes one of the main components of the productive forces of the state. Therefore, the well-being and welfare of the entire society in the future depend on its thriving development. Despite significant accumulated knowledge in medicine, there are still some white spots that are difficult to analyze and predict. The use of artificial intelligence and neural networks in healthcare can significantly expand the analytical apparatus and radically change the existing approaches to scientific research. This article discusses the results of the practical application of artificial intelligence and artificial neural networks in healthcare. The research aims to demonstrate the prospects and advantages of using these information technologies in medicine; identify problems in the implementation of AI technologies in medical practice and offer possible solutions to some of them. The authors provide a comprehensive literature review on the issues of artificial intelligence and neural networks, consider successful examples of the AI use in pharmacology, forecasting, and research of various types of diseases, including cardiovascular system, dermatology, and oncology. A significant part of the research is devoted to ethical and legal concerns, as well as problems associated with the practical use of artificial intelligence. As a result of the research, the authors suggest the models of the IT architecture of a medical information system and data flows, based on the TOGAF standard.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>healthcare</kwd>
        <kwd>artificial intelligence</kwd>
        <kwd>artificial neural networks</kwd>
        <kwd>diagnosis and prediction</kwd>
        <kwd>TOGAF standard</kwd>
        <kwd>medical information system</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
