Intelligent Prediction of Cryptogenic Stroke Using Patent Foramen Ovale from TEE Imaging Data and Machine Learning Methods

Intelligent Prediction of Cryptogenic Stroke Using Patent Foramen Ovale from TEE Imaging Data and Machine Learning Methods

Abstract In spite of the popularity of random forests (RF) as an efficient machine learning algorithm, methods for constructing the potential association for between patent foramen ovale (PFO) and cryptogenic stroke (CS) using this technique are still barely. For the vital regional study areas (atri...

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Bibliographic Details
Main Authors: Jiao Bai, Jia Yang, Wanwan Song, Yumin Liu, Haibo Xu, Yang Liu
Format: Article
Language:English
Published: Springer 2022-02-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Multi-Doppler sensor
Random forest
Patent foramen ovale
Cryptogenic stroke
Prediction diagnosis
Online Access:https://doi.org/10.1007/s44196-022-00067-8

Internet

https://doi.org/10.1007/s44196-022-00067-8

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