Predicting Continuity of Asthma Care Using a Machine Learning Model: Retrospective Cohort Study
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Hamed Asadi & Richard Dowling & Bernard Yan & Peter Mitchell, 2014. "Machine Learning for Outcome Prediction of Acute Ischemic Stroke Post Intra-Arterial Therapy," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Wenjuan Wang & Martin Kiik & Niels Peek & Vasa Curcin & Iain J Marshall & Anthony G Rudd & Yanzhong Wang & Abdel Douiri & Charles D Wolfe & Benjamin Bray, 2020. "A systematic review of machine learning models for predicting outcomes of stroke with structured data," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
- Yizhao Ni & Kathleen Alwell & Charles J Moomaw & Daniel Woo & Opeolu Adeoye & Matthew L Flaherty & Simona Ferioli & Jason Mackey & Felipe De Los Rios La Rosa & Sharyl Martini & Pooja Khatri & Dawn Kle, 2018. "Towards phenotyping stroke: Leveraging data from a large-scale epidemiological study to detect stroke diagnosis," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-20, February.
- Esra Zihni & Vince Istvan Madai & Michelle Livne & Ivana Galinovic & Ahmed A Khalil & Jochen B Fiebach & Dietmar Frey, 2020. "Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
- Wieslaw L Nowinski & Varsha Gupta & Guoyu Qian & Wojciech Ambrosius & Radoslaw Kazmierski, 2014. "Population-Based Stroke Atlas for Outcome Prediction: Method and Preliminary Results for Ischemic Stroke from CT," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
More about this item
Keywords
continuity of care; asthma; predicting; feature engineering; machine learning; retrospective study;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1237-:d:731057. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.