Fast and noninvasive electronic nose for sniffing-out COVID-19 based on exhaled breath-print recognition
Penulis/Author
dr. Dian Kesumapramudya Nurputra, M.Sc, Ph.D, SpA (1); Dr.Eng. Ahmad Kusumaatmaja, S.Si., M.Sc. (2); dr. Mohamad Saifudin Hakim, M.Sc, Ph.D. (3); SHIDIQ NUR HIDAYAT (4); TRISNA JULIAN (5); BUDI SUMANTO (6); Prof. dr. Yodi Mahendradhata, M.Sc., Ph.D., FRSPH. (7); dr. Antonia Morita Iswari Saktiawati., Ph.D (8); Hutomo Suryo Wasisto (9); Prof. Dr. Eng. Kuwat Triyana, M.Si. (10)
Tanggal/Date
16 2022
Kata Kunci/Keyword
Abstrak/Abstract
Despite its high accuracy to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),
the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach possesses several
limitations (e.g., the lengthy invasive procedure, the reagent availability, and the requirement of
specialized laboratory, equipment, and trained staffs). We developed and employed a low-cost,
noninvasive method to rapidly sniff out the coronavirus disease 2019 (COVID-19) based on a portable
electronic nose (GeNose C19) integrating metal oxide semiconductor gas sensor array, optimized feature
extraction, and machine learning models. This approach was evaluated in profiling tests involving a total
number of 615 breath samples (i.e., 333 positive and 282 negative COVID-19 confirmed by RT-qPCR)
obtained from 83 patients in two hospitals located in the Special Region of Yogyakarta, Indonesia. Four
different machine learning algorithms (i.e., linear discriminant analysis (LDA), support vector machine
(SVM), stacked multilayer perceptron (MLP), and deep neural network (DNN)) were utilized to identify the
top-performing pattern recognition methods and to obtain high system detection accuracy (88–95%),
sensitivity (86–94%), specificity (88–95%) levels from the testing datasets. Our results suggest that
GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.
Rumpun Ilmu
Ilmu Kedokteran Klinik
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
s41746-022-00661-2.pdf
[PAK] Full Dokumen
2
Fast and noninvasive electronic nose for sniffing-out COVID-19 based on exhaled breath-print recognition.pdf
[PAK] Cek Similarity
3
Dokumen Korespondensi Paper GeNose NPJDigital MEdicine.pdf
[PAK] Bukti Korespondensi Penulis
4
Similarity_Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition.pdf
