Real-Time Breath Analysis for COPD Risk Assessment in Smokers Using a ZnO/SnO₂ Heterojunction Sensor Integrated with Support Vector Machine
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2025
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| _version_ | 1866902089385377792 |
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| author | C, Poundoss Savarimuthu, Kirubaveni Mohammed, Gulam Nabi Alsath R, Krishnamoorthy T, Yuvaraj Bajaj, Mohit Shabaz, Mohammad |
| author_facet | C, Poundoss Savarimuthu, Kirubaveni Mohammed, Gulam Nabi Alsath R, Krishnamoorthy T, Yuvaraj Bajaj, Mohit Shabaz, Mohammad |
| contents | <p>This dataset contains real-time resistance values of a ZnO/SnO₂-based respiratory sensor recorded during human breath analysis. The data supports the study on COPD risk assessment and is intended for open research use</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15655842 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Real-Time Breath Analysis for COPD Risk Assessment in Smokers Using a ZnO/SnO₂ Heterojunction Sensor Integrated with Support Vector Machine C, Poundoss Savarimuthu, Kirubaveni Mohammed, Gulam Nabi Alsath R, Krishnamoorthy T, Yuvaraj Bajaj, Mohit Shabaz, Mohammad Breath analysis, Carbon monoxide sensor, COPD detection, Exhaled biomarkers, Gas sensing, Internet of Things, Machine learning, Metal oxide heterojunction, Support Vector Machine, Wearable health monitoring <p>This dataset contains real-time resistance values of a ZnO/SnO₂-based respiratory sensor recorded during human breath analysis. The data supports the study on COPD risk assessment and is intended for open research use</p> |
| title | Real-Time Breath Analysis for COPD Risk Assessment in Smokers Using a ZnO/SnO₂ Heterojunction Sensor Integrated with Support Vector Machine |
| topic | Breath analysis, Carbon monoxide sensor, COPD detection, Exhaled biomarkers, Gas sensing, Internet of Things, Machine learning, Metal oxide heterojunction, Support Vector Machine, Wearable health monitoring |
| url | https://doi.org/10.5281/zenodo.15655842 |