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A Clinical Breathomics Dataset

Authors :
Ping-Hung Kuo
Yue-Chen Jhong
Tien-Chueh Kuo
Yu-Ting Hsu
Ching-Hua Kuo
Yufeng Jane Tseng
Source :
Scientific Data, Vol 11, Iss 1, Pp 1-6 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient’s breath, thereby augmenting future diagnostic and therapeutic initiatives.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.0645a9581d7a47478c2c7bfdae73cd68
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-024-03052-2