IDEAS home Printed from https://ideas.repec.org/a/bjb/journl/v15y2026i5p950-957.html

Severity Prediction of Poliomyelitis Using Mathematical Model

Author

Listed:
  • Pradnya S. Doke

    (Department of Computer Science, Yashwantrao Chavan Institute of Science, Satara, India)

  • Bharat. T. Jadhav

    (Department of Electronics, Yashwantrao Chavan Institute of Science, Satara, India)

  • S. V. Nikam

    (Department of Electronics, Yashwantrao Chavan Institute of Science, Satara, India)

  • Rutuja B. Jadhav

    (Dr. Ravi Patil Institute of Physiotherapy, Belgavi, Karnataka)

Abstract

The major challenge in severity detection of poliomyelitis is its stealthy nature. Hence in this research work Mathematical models have been developed to predict severity of poliomyelitis. presents a comparison of Mathematical models for Severity Prediction of Poliomyelitis. Three Mathematical models were developed viz. Ordinary Differential Equations (ODE), Partial Differential Equations (PDE), and Agent-Based Models (ABM) by using MATLAB IDE. These models show the disease progression in the body from different points of view. These models give a severity score from 0 to 5. It uses patient age and symptoms like fever temperature, muscle strength, reflex score, and breathing condition as input. We trained these mathematical models using records of 1,500 patient, it shows 92% average in predicting the severity level of Poliomyelitis. It supports the doctors to check the severity-level of Poliomyelitis.

Suggested Citation

  • Pradnya S. Doke & Bharat. T. Jadhav & S. V. Nikam & Rutuja B. Jadhav, 2026. "Severity Prediction of Poliomyelitis Using Mathematical Model," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 15(5), pages 950-957, May.
  • Handle: RePEc:bjb:journl:v:15:y:2026:i:5:p:950-957
    as

    Download full text from publisher

    File URL: https://www.ijltemas.in/submission/online/article/view/4794/6498
    Download Restriction: no

    File URL: https://www.ijltemas.in/submission/online/article/view/4794/6499
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjb:journl:v:15:y:2026:i:5:p:950-957. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.