Detection of Infectious Respiratory Disease Through Sweat From Axillary Using an E-Nose With Stacked Deep Neural Network-Reference-Cited by-同舟云学术

Detection of Infectious Respiratory Disease Through Sweat From Axillary Using an E-Nose With Stacked Deep Neural Network

Published:2022 Issue: Volume:10 Page:51285-51298
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Malikhah ¹^ORCID,Sarno Riyanarto¹^ORCID,Inoue Sozo²^ORCID,Ardani M. Syauqi Hanif¹,Purbawa Doni Putra¹,Sabilla Shoffi Izza¹,Sungkono Kelly Rossa¹^ORCID,Fatichah Chastine¹^ORCID,Sunaryono Dwi¹,Bakhtiar Arief³,Libriansyah ⁴,Prakoeswa Cita R. S.⁵,Tinduh Damayanti⁶,Hernaningsih Yetti⁷

Affiliation:

1. Department of Informatics, Faculty of Intelligent Electrical and Informatics Technology, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Sukolilo, Indonesia

2. Department of Human Intelligence Systems, Kyushu Institute of Technology, Fukuoka, Japan

3. Department of Pulmonology, Faculty of Medicine, Airlangga University, Surabaya, Indonesia

4. Department of Internal Medicine, Dr. Ramelan Navy Hospital, Surabaya, Indonesia

5. Department of Dermatology and Venerology, Faculty of Medicine, Airlangga University, Surabaya, Indonesia

6. Department of Physical Medical and Rehabilitation, Faculty of Medicine, Airlangga University, Surabaya, Indonesia

7. Department of Clinical Pathology, Faculty of Medicine, Airlangga University, Surabaya, Indonesia

Funder

Direktorat Riset dan Pengabdian Masyarakat

Directorate General of Higher Education, Research, and Technology

Indonesian Ministry of Education, Culture, Research and Technology through the Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT) Program

Institut Teknologi Sepuluh Nopember (ITS) through the Project Scheme of the Publication Writing and IPR Incentive Program

Indonesian Ministry of Education, Culture, Research and Technology through the Matching Fund (MF) Kedaireka Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09771223.pdf?arnumber=9771223

Reference28 articles.

1. SARS-CoV-2 is not found in the sweat of COVID-19 positive patients

2. Recognition of Original Arabica Civet Coffee based on Odor using Electronic Nose and Machine Learning

3. Detection and Classification of Indonesian Civet and Non-Civet Coffee Based on Statistical Analysis Comparison Using E-Nose

4. Ensemble Learning for Optimizing Classification of Pork Adulteration in Beef Based on Electronic Nose Dataset

5. Detecting Pork Adulteration in Beef for Halal Authentication Using an Optimized Electronic Nose System

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