<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-information-and-optimization-sciences</journal-id>
      <journal-title-group>
        <journal-title>Journal of Information and Optimization Sciences</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0103</issn>
      <issn publication-format="print">0252-2667</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JIOS-1865</article-id>
      <title-group>
        <article-title>Deep learning and probabilistic neural networks-based identification and classification of Pneumonia-related lung diseases</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Vinothkumar</surname>
            <given-names>N.</given-names>
          </name>
          <aff>Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rao</surname>
            <given-names>Ch. Madhava</given-names>
          </name>
          <aff>Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Nitnaware</surname>
            <given-names>Swati R.</given-names>
          </name>
          <aff>Department of Electronics Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharastra, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Shakunthala</surname>
            <given-names>M.</given-names>
          </name>
          <aff>Department of Electronics and Communication Engineering, Kavaraipettai, R.M.D. Engineering College, Thiruvallur, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Shahnaz</surname>
            <given-names>K. V.</given-names>
          </name>
          <aff>Department of Electronics and Communication Engineering, Veltech Rangarajan Dr. Sagunthala R&amp;D Institute of Science and Technology, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Sreevidya</surname>
            <given-names>Nelli</given-names>
          </name>
          <aff>Department of Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad, Telangana, India</aff>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Bhagyalakshmi</surname>
            <given-names>L.</given-names>
          </name>
          <aff>Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Kumar</surname>
            <given-names>Nitesh</given-names>
          </name>
          <aff>Department of Information Technology, L. N. Mishra College of Business Management, Muzaffarpur, Bihar, India</aff>
        </contrib>
      </contrib-group>
      <volume>46</volume>
      <issue>1</issue>
      <fpage>213</fpage>
      <lpage>222</lpage>
      <pub-date date-type="pub">
        <day>19</day>
        <month>02</month>
        <year>2025</year>
      </pub-date>
      <abstract>
        <p>In every part of the world, lung disease is a major issue. Early lung disease identification is crucial. A variety of deep learning techniques, such as convolutional neural networks (CNNs), Visual Geometry Group (VGG) networks, capsule networks, and traditional neural networks, are commonly employed for predicting lung diseases. Since the emergence of the novel COVID-19, extensive research has been conducted to explore its ability to make precise predictions. Given that many fatalities were attributed to severe chest congestion, Pneumonia an early-stage lung condition is likely closely associated with COVID-19 (pneumonic condition). Medical professionals may find it difficult to differentiate COVID-19 from other lung diseases, such as Pneumonia.</p>
      </abstract>
      <kwd-group>
        <kwd>CNN</kwd>
        <kwd>Novel COVID-19</kwd>
        <kwd>Data source</kwd>
        <kwd>Data gathering</kwd>
        <kwd>Image quality enhancement</kwd>
        <kwd>Adaptive</kwd>
        <kwd>Precise region of interest (ROI) evaluation</kwd>
        <kwd>Characteristic extraction</kwd>
        <kwd>Disease prediction</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
