A cross-sectional study: a breathomics based pulmonary tuberculosis detection method
Key messages What is already known on this topic—Breath VOC analysis is a potential technology for PTB detection. However, it is still desirable for a real-time, robust, accurate, and simple breath analysis platform for clinical application. What this study adds—An online breath detection for PTB wa...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-03-01
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| Series: | BMC Infectious Diseases |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12879-023-08112-3 |
| _version_ | 1797865455654797312 |
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| author | Liang Fu Lei Wang Haibo Wang Min Yang Qianting Yang Yi Lin Shanyi Guan Yongcong Deng Lei Liu Qingyun Li Mengqi He Peize Zhang Haibin Chen Guofang Deng |
| author_facet | Liang Fu Lei Wang Haibo Wang Min Yang Qianting Yang Yi Lin Shanyi Guan Yongcong Deng Lei Liu Qingyun Li Mengqi He Peize Zhang Haibin Chen Guofang Deng |
| author_sort | Liang Fu |
| collection | DOAJ |
| description | Key messages What is already known on this topic—Breath VOC analysis is a potential technology for PTB detection. However, it is still desirable for a real-time, robust, accurate, and simple breath analysis platform for clinical application. What this study adds—An online breath detection for PTB was proposed and demonstrated with high sensitivity and specificity in a large clinical cohort. How this study might affect research, practice, or policy—This study may promote the application of breath detection in clinical TB detection and related biomarker studies. |
| first_indexed | 2024-04-09T23:08:12Z |
| format | Article |
| id | doaj.art-19bd7f1429574e9ab6ea7addea9c0028 |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-04-09T23:08:12Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj.art-19bd7f1429574e9ab6ea7addea9c00282023-03-22T10:32:09ZengBMCBMC Infectious Diseases1471-23342023-03-0123111110.1186/s12879-023-08112-3A cross-sectional study: a breathomics based pulmonary tuberculosis detection methodLiang Fu0Lei Wang1Haibo Wang2Min Yang3Qianting Yang4Yi Lin5Shanyi Guan6Yongcong Deng7Lei Liu8Qingyun Li9Mengqi He10Peize Zhang11Haibin Chen12Guofang Deng13Division Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyBreax Laboratory, PCAB Research Center of Breath and MetabolismPeking University Clinical Research Institute, Peking University First HospitalDivision Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyInstitute for Hepatology, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyDivision Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyMedical Examination Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyPulmonary Diseases Out-Patient Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyDivision Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyBreax Laboratory, PCAB Research Center of Breath and MetabolismBreax Laboratory, PCAB Research Center of Breath and MetabolismDivision Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyBreax Laboratory, PCAB Research Center of Breath and MetabolismDivision Two of the Pulmonary Diseases Department, The Third People’s Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, Southern University of Science and TechnologyKey messages What is already known on this topic—Breath VOC analysis is a potential technology for PTB detection. However, it is still desirable for a real-time, robust, accurate, and simple breath analysis platform for clinical application. What this study adds—An online breath detection for PTB was proposed and demonstrated with high sensitivity and specificity in a large clinical cohort. How this study might affect research, practice, or policy—This study may promote the application of breath detection in clinical TB detection and related biomarker studies.https://doi.org/10.1186/s12879-023-08112-3Pulmonary tuberculosisMachine learningVolatile organic compoundsBreathomics |
| spellingShingle | Liang Fu Lei Wang Haibo Wang Min Yang Qianting Yang Yi Lin Shanyi Guan Yongcong Deng Lei Liu Qingyun Li Mengqi He Peize Zhang Haibin Chen Guofang Deng A cross-sectional study: a breathomics based pulmonary tuberculosis detection method BMC Infectious Diseases Pulmonary tuberculosis Machine learning Volatile organic compounds Breathomics |
| title | A cross-sectional study: a breathomics based pulmonary tuberculosis detection method |
| title_full | A cross-sectional study: a breathomics based pulmonary tuberculosis detection method |
| title_fullStr | A cross-sectional study: a breathomics based pulmonary tuberculosis detection method |
| title_full_unstemmed | A cross-sectional study: a breathomics based pulmonary tuberculosis detection method |
| title_short | A cross-sectional study: a breathomics based pulmonary tuberculosis detection method |
| title_sort | cross sectional study a breathomics based pulmonary tuberculosis detection method |
| topic | Pulmonary tuberculosis Machine learning Volatile organic compounds Breathomics |
| url | https://doi.org/10.1186/s12879-023-08112-3 |
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