Machine Learning for Outcome Prediction of Acute Ischemic Stroke Post Intra-Arterial Therapy
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DOI: 10.1371/journal.pone.0088225
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Cited by:
- Yao Tong & Beilei Lin & Gang Chen & Zhenxiang Zhang, 2022. "Predicting Continuity of Asthma Care Using a Machine Learning Model: Retrospective Cohort Study," IJERPH, MDPI, vol. 19(3), pages 1-18, January.
- 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.
- 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.
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