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Journal of Asthma Volume 58, 2021 - Issue 11
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Management and Control

Detecting asthma exacerbations using daily home monitoring and machine learning

Olivier Zhanga Department of Computer Engineering (INFO), INSA Rennes, Rennes, FranceView further author information
, MEng,
Leandro L. Minkub School of Computer Science, University of Birmingham, UKView further author information
, PhD &
Sherif Gonemc Department of Respiratory Medicine, Nottingham City Hospital, Nottingham, UK;d Department of Respiratory Science, University of Leicester, Leicester, UKCorrespondence[email protected]
View further author information
, PhD
Pages 1518-1527 | Received 27 Apr 2020, Accepted 24 Jul 2020, Published online: 14 Aug 2020

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Kevin C H Tsang, Hilary Pinnock, Andrew M Wilson & Syed Ahmar Shah. (2022) Application of Machine Learning Algorithms for Asthma Management with mHealth: A Clinical Review. Journal of Asthma and Allergy 15, pages 855-873.
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Articles from other publishers (13)

Widana Kankanamge Darsha Jayamini, Farhaan Mirza, M. Asif Naeem & Amy Hai Yan Chan. (2024) Investigating Machine Learning Techniques for Predicting Risk of Asthma Exacerbations: A Systematic Review. Journal of Medical Systems 48:1.
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Xenofon Aggelidis, Maria Kritikou, Michael Makris, Michael Miligkos, Niki Papapostolou, Nikolaos G. Papadopoulos & Paraskevi Xepapadaki. (2024) Tele-Monitoring Applications in Respiratory Allergy. Journal of Clinical Medicine 13:3, pages 898.
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Nestor A. Molfino, Gianluca Turcatel & Daniel Riskin. (2023) Machine Learning Approaches to Predict Asthma Exacerbations: A Narrative Review. Advances in Therapy 41:2, pages 534-552.
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Sherif Gonem. 2024. Artificial Intelligence in Clinical Practice. Artificial Intelligence in Clinical Practice 127 135 .
Rose Yemson, Sohag Kabir, Dhavalkumar Thakker & Savas Konur. (2023) Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring. Computers 12:11, pages 238.
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Nikita Savvin, Dmitrii Vasenin, Semyen Podvalny, Marco Pasetti, Stefano Rinaldi & Victoria Lesina. (2023) Tools for Analysis of Treatment Dynamics and Outcomes for Personalized Medicine in Asthma. Tools for Analysis of Treatment Dynamics and Outcomes for Personalized Medicine in Asthma.
Merlijn van Breugel, Rudolf S. N. Fehrmann, Marnix Bügel, Faisal I. Rezwan, John W. Holloway, Martijn C. Nawijn, Sara Fontanella, Adnan Custovic & Gerard H. Koppelman. (2023) Current state and prospects of artificial intelligence in allergy. Allergy 78:10, pages 2623-2643.
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Apeksha Koul, Rajesh K. Bawa & Yogesh Kumar. (2022) Artificial Intelligence Techniques to Predict the Airway Disorders Illness: A Systematic Review. Archives of Computational Methods in Engineering 30:2, pages 831-864.
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K S Kavitha, M Monisha, M Nischitha, M Nisha & A Raksitha. (2023) Asthma prediction and monitoring. Indian Journal of Allergy, Asthma and Immunology 37:2, pages 33-36.
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Sudha, Harkesh Sehrawat, Yudhvir Singh & Vivek Jaglan. 2023. Advances in Data-Driven Computing and Intelligent Systems. Advances in Data-Driven Computing and Intelligent Systems 335 346 .
Kevin Cheuk Him Tsang, Hilary Pinnock, Andrew M Wilson, Dario Salvi & Syed Ahmar Shah. (2022) Predicting asthma attacks using connected mobile devices and machine learning: the AAMOS-00 observational study protocol. BMJ Open 12:10, pages e064166.
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Apeksha Koul, Rajesh K. Bawa & Yogesh Kumar. 2022. Connected e-Health. Connected e-Health 217 254 .
Barbara Putman, Lies Lahousse, David G. Goldfarb, Rachel Zeig-Owens, Theresa Schwartz, Ankura Singh, Brandon Vaeth, Charles B. Hall, Elizabeth A. Lancet, Mayris P. Webber, Hillel W. Cohen, David J. Prezant & Michael D. Weiden. (2020) Factors Predicting Treatment of World Trade Center-Related Lung Injury: A Longitudinal Cohort Study. International Journal of Environmental Research and Public Health 17:23, pages 9056.
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