Prediction Optimization of Cervical Hyperextension Injury: Kernel Extreme Learning Machines With Orthogonal Learning Butterfly Optimizer and Broyden- Fletcher-Goldfarb-Shanno Algorithms

Prediction Optimization of Cervical Hyperextension Injury: Kernel Extreme Learning Machines With Orthogonal Learning Butterfly Optimizer and Broyden- Fletcher-Goldfarb-Shanno Algorithms

In this research, X-ray and MRI images of patients suffering from cervical hyperextension injury are investigated. Also, radiographic images are collected from patients who suffered from trauma but without cervical hyperextension injury. The core engine algorithm of the optimized prediction model is...

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Bibliographic Details
Main Authors: Guomin Liu, Wenyuan Jia, Yungang Luo, Mingjing Wang, Ali Asghar Heidari, Jinsheng Ouyang, Huiling Chen, Mayun Chen
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Butterfly optimization algorithm
medical diagnosis
kernel extreme learning machine
parameter optimization
global optimization
Online Access:https://ieeexplore.ieee.org/document/9120017/

Internet

https://ieeexplore.ieee.org/document/9120017/

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