A systematic review of machine learning models for predicting outcomes of stroke with structured data
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Abstract
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DOI: 10.1371/journal.pone.0234722
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References listed on IDEAS
- Ben Van Calster & Andrew J. Vickers, 2015. "Calibration of Risk Prediction Models," Medical Decision Making, , vol. 35(2), pages 162-169, February.
- 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.
- Geert-Jan Geersing & Walter Bouwmeester & Peter Zuithoff & Rene Spijker & Mariska Leeflang & Karel Moons, 2012. "Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-6, February.
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- Marcel Lucas Chee & Marcus Eng Hock Ong & Fahad Javaid Siddiqui & Zhongheng Zhang & Shir Lynn Lim & Andrew Fu Wah Ho & Nan Liu, 2021. "Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review," IJERPH, MDPI, vol. 18(9), pages 1-15, April.
- Ching-Heng Lin & Ya-Wen Kuo & Yen-Chu Huang & Meng Lee & Yi-Wei Huang & Chang-Fu Kuo & Jiann-Der Lee, 2023. "Development and Validation of a Novel Score for Predicting Long-Term Mortality after an Acute Ischemic Stroke," IJERPH, MDPI, vol. 20(4), pages 1-12, February.
- Vieira, Bruno Hebling & Pamplona, Gustavo Santo Pedro & Fachinello, Karim & Silva, Alice Kamensek & Foss, Maria Paula & Salmon, Carlos Ernesto Garrido, 2022. "On the prediction of human intelligence from neuroimaging: A systematic review of methods and reporting," Intelligence, Elsevier, vol. 93(C).
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