A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.

Journal: Clinica chimica acta; international journal of clinical chemistry
PMID: 39326694

Abstract

BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality rates among newborns. Recognizing the profound impact of neonatal sepsis on long-term health outcomes emphasizes the critical need for timely detection to mitigate its consequences and ensure optimal health for the affected newborns. Currently, various diagnostic approaches have been implemented, but they are limited by their invasiveness, high costs, centralized testing, frequent delays, inaccuracies in results, and the need for sophisticated laboratory equipment.

Authors

  • Kombo Othman Kombo
    Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta 55281, Indonesia; Department of Natural Sciences, College of Science and Technical Education, Mbeya University of Science and Technology, P.O.Box 131, Mbeya, Tanzania.
  • Shidiq Nur Hidayat
    Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta 55281, Indonesia.
  • Mayumi Puspita
    Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta 55281, Indonesia.
  • Ahmad Kusumaatmaja
    Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta 55281, Indonesia.
  • Roto Roto
    Chemistry Department, Faculty of Mathematic and Natural Sciences, Gadjah Mada University, Sekip Utara PO. Box Bls 21, Yogyakarta, 55281, Indonesia.
  • Hera Nirwati
    Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia.
  • Rina Susilowati
    Department of Histology and Cell Biology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia.
  • Ekawaty Lutfia Haksari
    Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
  • Tunjung Wibowo
    Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
  • Setya Wandita
    Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
  • Wahyono
    Department of Computer Science and Electronics, Universitas Gadjah Mada, Sekip Utara BLS 21, 55281 Yogyakarta, Indonesia.
  • Madarina Julia
    Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
  • Kuwat Triyana
    Department of Physics, Universitas Gadjah Mada, Sekip Utara Yogyakarta, 55281 Indonesia.

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