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  <doi_batch_id>aspg-18-2684-1792025807</doi_batch_id>
  <timestamp>20261015005647</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>Journal of Intelligent Systems and Internet of Things</full_title>
    <abbrev_title>JISIoT</abbrev_title>
    <issn media_type="print">2769-786X</issn>
    <issn media_type="electronic">2690-6791</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>12</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Quantitative Approach for Anemia Detection Using Regression Analysis</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Vinit P.</given_name>
      <surname>Kharkar</surname>
      <affiliations>
       <institution>
        <institution_name>Assistant Professor, Department of Electronics &amp; Telecommunication Engineering, Prof Ram Meghe College of Engineering and Management, Badnera-Amravati, MH, India.</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Ajay P.</given_name>
      <surname>Thakare</surname>
      <affiliations>
       <institution>
        <institution_name>Professor, Department of Electronics &amp; Telecommunication Engineering, Sipna College of Engineering and Technology, Amravati, MH, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Anemia, generally termed as deficiency of hemoglobin or red blood cells in the blood is significant global health concern for the population in underdeveloped as well as in developing nations specially, for children and young women in rural areas. This paper proposes a quantitative approach for anemia detection by regression analysis technique which predicts hemoglobin level in the blood. To achieve this, the image dataset of microscopic blood sample is collected from 70 individuals. The data collection requires proper procedure as it plays vital part in system implementation. The statistical feature utilizing mean pixel intensity values from the red, green, and blue color planes of the images are given as input to the regression model. For the proposed system, we have employed multiple regression analysis model using machine learning approach with both three and four regression coefficients to establish relation between features obtained from blood samples and the hemoglobin level in the blood to achieve the specified task of anemia detection in an individual. Performance analysis show promising results for the proposed system with co-efficient of determination (R2) and root mean square error (RMSE) found out be 0.923 and 1.682 respectively. Overall, this paper presents valuable system for anemia detection based on hemoglobin estimation which can be implemented in areas with limited medical resources and gives another supportive technological solution for current healthcare problems.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>34</first_page>
     <last_page>43</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2684</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/JISIoT.120203</doi>
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