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<Articles JournalTitle="Iranian Journal of Public Health">
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Iranian Journal of Public Health</JournalTitle>
      <Issn>2251-6085</Issn>
      <Volume>54</Volume>
      <Issue>10</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Advancing Cervical Cancer Care: A Comprehensive Study of Screening Approach for Tribal Women in Sub-Saharan Africa and Asia</title>
    <FirstPage>2151</FirstPage>
    <LastPage>2160</LastPage>
    <AuthorList>
      <Author>
        <FirstName>Jennyfer Susan Maliakkal</FirstName>
        <LastName>Babu</LastName>
        <affiliation locale="en_US">Department of Computer Science, Centre for Machine Learning and Intelligence, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India</affiliation>
      </Author>
      <Author>
        <FirstName>Parthasarathy</FirstName>
        <LastName>Subashini</LastName>
        <affiliation locale="en_US">Department of Computer Science, Centre for Machine Learning and Intelligence, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India</affiliation>
      </Author>
      <Author>
        <FirstName>Thookanayakanpalayam Thyagarajan</FirstName>
        <LastName>Dhivyaprabha</LastName>
        <affiliation locale="en_US">Department of Computer Science, Centre for Machine Learning and Intelligence, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2024</Year>
        <Month>12</Month>
        <Day>26</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2025</Year>
        <Month>05</Month>
        <Day>17</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background: Cervical cancer is one of the leading causes of cancer-related mortality among women in developing regions, particularly within tribal populations of Sub-Saharan Africa and Asia. This study aimed to evaluate existing screening strategies in tribal communities, compare them with global best practices, and explore the feasibility of smart colposcopy as an effective screening tool in low-resource settings.
Methods: A mixed-methods approach was employed, combining systematic literature review 2000-2024, case study analysis, and technical evaluation. Data were collected from peer-reviewed journals, healthcare databases, and open-access medical image repositories. The diagnostic utility and usability of smart colposcopy using the Eva System were assessed. Advanced image processing techniques, including CNN-based detection and partial convolution inpainting, were applied to improve visual clarity by mitigating artifacts like specular reflection.
Results: Findings reveal significant screening barriers in tribal regions, such as fear, stigma, and infrastructural deficits. Compared to structured programs in developed countries, tribal areas show lower compliance. Smart colposcopy demonstrated high potential for remote screening due to its portability and real-time AI support. Image quality enhancements improved diagnostic accuracy.
Conclusion: Smart colposcopy, integrated with awareness initiatives and supportive policies, offers a scalable solution to improve early detection and reduce cervical cancer mortality in tribal and underserved populations.</abstract>
    <web_url>https://ijph.tums.ac.ir/index.php/ijph/article/view/37588</web_url>
    <pdf_url>https://ijph.tums.ac.ir/index.php/ijph/article/download/37588/8674</pdf_url>
  </Article>
</Articles>
