Using dynamics of forced expiration to identify COPD where conventional criteria for the FEV 1 / FVC ratio do not match
Detailed mathematical analysis of expiratory flow dynamics in combination with support vector machine is able to detect airflow limitation and characterize presence of COPD. This methodology allows better identification of subjects with or without COPD characteristics when other spirometry‐based cri...
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Published in | Respirology (Carlton, Vic.) Vol. 20; no. 6; pp. 925 - 931 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
01.08.2015
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Online Access | Get full text |
ISSN | 1323-7799 1440-1843 |
DOI | 10.1111/resp.12540 |
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Abstract | Detailed mathematical analysis of expiratory flow dynamics in combination with support vector machine is able to detect airflow limitation and characterize presence of COPD. This methodology allows better identification of subjects with or without COPD characteristics when other spirometry‐based criteria and specific cut‐offs do not confirm COPD. |
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AbstractList | Detailed mathematical analysis of expiratory flow dynamics in combination with support vector machine is able to detect airflow limitation and characterize presence of COPD. This methodology allows better identification of subjects with or without COPD characteristics when other spirometry‐based criteria and specific cut‐offs do not confirm COPD. |
Author | Janssens, Wim Troosters, Thierry Decramer, Marc Exadaktylos, Vasileios Topalovic, Marko Berckmans, Daniel |
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CitedBy_id | crossref_primary_10_1016_j_rmed_2019_08_004 crossref_primary_10_1111_resp_12771 crossref_primary_10_1016_j_resp_2015_12_002 crossref_primary_10_3390_biomedicines10040786 crossref_primary_10_4103_jfmpc_jfmpc_1052_24 crossref_primary_10_1016_j_resp_2016_02_002 crossref_primary_10_1097_MCP_0000000000000459 crossref_primary_10_1016_j_cmpb_2019_105267 crossref_primary_10_1016_j_joca_2015_09_015 crossref_primary_10_4187_respcare_04850 |
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