A retrospective study using machine learning to develop predictive model to identify rotavirus-associated acute gastroenteritis in children.

Journal: PeerJ
PMID: 40247842

Abstract

BACKGROUND: Rotavirus is the leading cause of severe dehydrating diarrhea in children under 5 years worldwide. Timely diagnosis is critical, but access to confirmatory testing is limited in hospital settings. Machine learning (ML) models have shown promising potential in supporting symptom-based diagnosis of several diseases in resource-limited settings.

Authors

  • Sourav Paul
    Department of Biotechnology, National Institute of Technology, Durgapur, West Bengal, India.
  • Minhazur Rahman
    Department of Computer Science and Engineering, Tezpur University, Tezpur, Napaam, Assam, India.
  • Anutee Dolley
    Department of Molecular Biology and Biotechnology, Tezpur University, Tezpur, Napaam, Assam, India.
  • Kasturi Saikia
    Department of Molecular Biology and Biotechnology, Tezpur University, Tezpur, Napaam, Assam, India.
  • Chongtham Shyamsunder Singh
    Department of Paediatrics, Regional Institute of Medical Sciences, Imphal, Manipur, India.
  • Arifullah Mohammed
    Department of Agriculture Science, Faculty of Agro-based Industry, Universiti Malaysia Kelantan, Kelantan, Malaysia.
  • Ghazala Muteeb
    Department of Nursing, College of Applied Medical Science, King Faisal University, Al-Ahsa, Saudi Arabia.
  • Rosy Sarmah
    Department of Computer Science and Engineering, Tezpur University, Napaam, Assam, India.
  • Nima D Namsa
    Department of Molecular Biology and Biotechnology, Tezpur University, Tezpur, Napaam, Assam, India.

Keywords

External Resources

Popular Topics
Recent Journals