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International Journal of Chronic Obstructive Pulmonary Disease Volume 12, 2017 - Issue
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Original Research

Identification of subtypes in subjects with mild-to-moderate airflow limitation and its clinical and socioeconomic implications

Jin Hwa Lee1 Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, EwhaWomans UniversityCorrespondence[email protected]
,
Chin Kook Rhee2 Department of Internal Medicine, Seoul St Mary’s Hospital, The Catholic University of Korea, Seoul
,
Kyungjoo Kim2 Department of Internal Medicine, Seoul St Mary’s Hospital, The Catholic University of Korea, Seoul
,
Jee-Ae Kim3 Pharmaceutical Policy Evaluation Research Team, Research Institution, Health Insurance Review and Assessment Service
,
Sang Hyun Kim4 Big Data Division, Health Insurance Review and Assessment Service, Wonju
,
Kwang Ha Yoo5 Department of Internal Medicine, Konkuk University College of Medicine, Seoul
,
Woo Jin Kim6 Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Chuncheon
,
Yong Bum Park7 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Hallym University Kangdong Sacred Heart Hospital
,
Hye Yun Park8 Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
&
Ki-Suck Jung9 Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Hallym University Medical Center, Hallym University College of Medicine, Anyang, South Korea
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Pages 1135-1144 | Published online: 12 Apr 2017

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Francis Nissen, Ian J Douglas, Hana Müllerová, Neil Pearce, Chloe I Bloom, Liam Smeeth & Jennifer K Quint. (2019) Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink). Journal of Asthma and Allergy 12, pages 7-19.
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Min-Hye Kim, Chin Kook Rhee, Kyungjoo Kim, Sang Hyun Kim, Jung Yeon Lee, Yee Hyung Kim, Kwang Ha Yoo, Young-Joo Cho, Ki-Suck Jung & Jin Hwa Lee. (2018) Heterogeneity of asthma and COPD overlap. International Journal of Chronic Obstructive Pulmonary Disease 13, pages 1251-1260.
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Rachel Nadif & Marine Savouré. 2023. Asthma in the 21st Century. Asthma in the 21st Century 1 30 .
Yong Suk Jo. (2022) Status of Studies Investigating Asthma–Chronic Obstructive Pulmonary Disease Overlap in Korea: A Review. Tuberculosis and Respiratory Diseases 85:2, pages 101-110.
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Caitlin E. Coombes, Xin Liu, Zachary B. Abrams, Kevin R. Coombes & Guy Brock. (2021) Simulation-derived best practices for clustering clinical data. Journal of Biomedical Informatics 118, pages 103788.
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Francisco Cunha, Rita Amaral, Tiago Jacinto, Bernardo Sousa-Pinto & João A. Fonseca. (2021) A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods. Diagnostics 11:4, pages 644.
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Vasilis Nikolaou, Sebastiano Massaro, Masoud Fakhimi, Lampros Stergioulas & David Price. (2020) COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda. Respiratory Medicine 171, pages 106093.
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Caitlin E Coombes, Zachary B Abrams, Suli Li, Lynne V Abruzzo & Kevin R Coombes. (2020) Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia. Journal of the American Medical Informatics Association 27:7, pages 1019-1027.
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Caitlin E. Coombes, Zachary B. Abrams, Samantha Nakayiza, Guy Brock & Kevin R. Coombes. (2021) Umpire 2.0: Simulating realistic, mixed-type, clinical data for machine learning. F1000Research 9, pages 1186.
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Caitlin E. Coombes, Zachary B. Abrams, Samantha Nakayiza, Guy Brock & Kevin R. Coombes. (2020) Umpire 2.0: Simulating realistic, mixed-type, clinical data for machine learning. F1000Research 9, pages 1186.
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