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Quantitative CT and Machine Learning-derived Hyper- and Hypo- Functional RegionsAssociate Heterogeneous Ventilation and Reduced Deformation With PFT and Smoking inCOPD
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 김은찬 | - |
| dc.date.accessioned | 2026-06-25T17:05:29Z | - |
| dc.date.available | 2026-06-25T17:05:29Z | - |
| dc.date.issued | 2025-05-19 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/217333 | - |
| dc.title | Quantitative CT and Machine Learning-derived Hyper- and Hypo- Functional RegionsAssociate Heterogeneous Ventilation and Reduced Deformation With PFT and Smoking inCOPD | - |
| dc.type | Conference | - |
| dc.citation.conferenceName | American Thoracic Society International Conference (ATS 2025) | - |
| dc.citation.conferencePlace | Moscone Center, San Francisco, CA, USA | - |
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Collections - 서울 공과대학 > 서울 정보시스템학과 > 2. Conference Papers
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- Kim, Eunchan
- COLLEGE OF ENGINEERING (DEPARTMENT OF INFORMATION SYSTEMS)