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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JPSIM</journal-id>
      <journal-title-group>
        <journal-title>Journal of Pakistan Society of Internal Medicine</journal-title>
        <abbrev-title>J Pak Soc Intern Med</abbrev-title>
      </journal-title-group>
      <issn publication-format="print">2709-8729</issn>
      <issn publication-format="electronic">2710-0804</issn>
      <publisher>
        <publisher-name>Pakistan Society of Internal Medicine</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.70302/jpsim.v5i1.2420</article-id>
      <article-id pub-id-type="publisher-id">jpsim.v5i1.2420</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Digital Health</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Revolutionising Wound Care Management Through Artificial Intelligence</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Tariq</surname>
            <given-names>Gulnaz</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Chughtai</surname>
            <given-names>Suhail</given-names>
          </name>
          <email>Director@MLProfessionals.com</email>
          <xref ref-type="aff" rid="aff2"/>
          <xref ref-type="corresp" rid="cor1">*</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <institution>Clinical Advisor Debra Pakistan</institution>
      </aff>
      <aff id="aff2">
        <institution>Consultant Orthopaedic Surgeon Medico-Legal Examiner, London, UK</institution>
      </aff>
      <author-notes>
        <corresp id="cor1">*Correspondence: Suhail Chughtai (Director@MLProfessionals.com)</corresp>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic" iso-8601-date="2024-02-28">
        <day>28</day>
        <month>02</month>
        <year>2024</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2024</year>
      </pub-date>
      <volume>5</volume>
      <issue>1</issue>
      <fpage>446</fpage>
      <lpage>451</lpage>
      <history>
        <date date-type="received" iso-8601-date="2023-10-13">
          <day>13</day>
          <month>10</month>
          <year>2023</year>
        </date>
        <date date-type="accepted" iso-8601-date="2023-11-30">
          <day>30</day>
          <month>11</month>
          <year>2023</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2024 The Author(s)</copyright-statement>
        <copyright-year>2024</copyright-year>
        <copyright-holder>The Author(s)</copyright-holder>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://psimj.com/article/jpsim.v5i1.2420" content-type="text/html"/>
      <self-uri xlink:href="https://psimj.com/article/jpsim.v5i1.2420.pdf" content-type="application/pdf"/>
      <abstract>
        <p>The management of wounds has been around for a long time. The traditional methods of wound care management were time-consuming, labour-intensive, and not efficient enough to cater to today's fast-moving world's needs. Integrating AI into wound care means greater efficiency, accuracy, and better outcomes. AI is an emerging healthcare technology that provides a unique opportunity to monitor chronic wounds by allowing doctors and nurses to capture high-quality images of wounds while enabling constant feedback to support early detection, diagnosis, and treatment. The computerised insight provided by the integration of AI steers a more personalised healing course, with healing times controlled based on various factors, such as wound type, size, and location. This insight builds into the multiple aspects of Artificial Intelligence that can best be used to track wounds' healing progress, signage of probable issues, and clinical hours spent by caregivers.</p>
      </abstract>
    </article-meta>
  </front>
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  <back>
    <ref-list>
      <title>References</title>
      <ref id="ref1">
        <label>1</label>
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      </ref>
      <ref id="ref2">
        <label>2</label>
        <mixed-citation>Direkoglu C, Nixon MS. The application of digital image processing and analysis to chronic wound assessment. Chron Wound Care Manage Res. 2016; 3(1): 101-111.</mixed-citation>
      </ref>
      <ref id="ref3">
        <label>3</label>
        <mixed-citation>Wang, S.H., Tran, K.N., Abu Affan, M. et al. A Benchmark Study on Deep Learning for Wound Tissue Segmentation. NPJ Digital Med. 2022; <pub-id pub-id-type="doi">10.1038/s41746-022-00557-5</pub-id></mixed-citation>
      </ref>
      <ref id="ref4">
        <label>4</label>
        <mixed-citation>Chino D, Meloni M, Dessi A. Artificial intelligence: a future option for the diagnosis and management of lower extremity ulcers. Journal of Wound Care 2022; 31(Sup2a): S1-S26.</mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>
