<?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-1563</article-id>
      <title-group>
        <article-title>Leveraging machine learning in healthcare : Exploring benefits and challenges</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Rajpoot</surname>
            <given-names>Navneet Kumar</given-names>
          </name>
          <aff>Department of Computer Science &amp; Engineering, Graphic Era (Deemed to be University), Dehradun, Dehradun, Uttrakhand, India</aff>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Singh</surname>
            <given-names>Prabh Deep</given-names>
          </name>
          <aff>Department of Computer Science &amp; Engineering, Graphic Era (Deemed to be University), Dehradun, Dehradun, Uttrakhand, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pant</surname>
            <given-names>Bhaskar</given-names>
          </name>
          <aff>Department of Computer Science &amp; Engineering, Graphic Era (Deemed to be University), Dehradun, Dehradun, Uttrakhand, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Tripathi</surname>
            <given-names>Vikas</given-names>
          </name>
          <aff>Department of Computer Science &amp; Engineering, Graphic Era (Deemed to be University), Dehradun, Dehradun, Uttrakhand, India</aff>
        </contrib>
      </contrib-group>
      <volume>45</volume>
      <issue>2</issue>
      <fpage>459</fpage>
      <lpage>467</lpage>
      <pub-date date-type="pub">
        <day>17</day>
        <month>03</month>
        <year>2024</year>
      </pub-date>
      <abstract>
        <p>Recent technology advancements have driven a technological shift in the healthcare industry. A vital component of this development is the increasing prominence of machine learning (ML) inside the medical industry’s framework. This study investigates the various uses, advantages, disadvantages, and issues related to machine learning (ML) in the healthcare sector. Personalized treatment plans and illness detection are just two of the many uses of machine learning thoroughly examined in this paper. This paper further explores the difficulties of data collecting, privacy and security concerns, and the effects of machine learning on healthcare efficiency and patient outcomes and future breakthroughs and new technology that could revolutionize healthcare. So that healthcare organizations can better figure out the possible revolutionary implications and challenges of machine learning (ML), this research explores these essential features of ML in the healthcare sector. One of the goals of this research is to create a future where healthcare is better and more patient-centered.</p>
      </abstract>
      <kwd-group>
        <kwd>Big data</kwd>
        <kwd>Internet of Things</kwd>
        <kwd>Efficiency</kwd>
        <kwd>Machine learning</kwd>
        <kwd>Smart healthcare</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>
