Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. MEDS Public Health and Preventive Medicine
  4. Vol 3, Issue 6, 2023

Prognostic study of hemorrhagic stroke patients based on GABP neural network model

Download as PDF

DOI: 10.23977/phpm.2023.030605 | Downloads: 8 | Views: 273

Author(s)

Anqi Wang 1,2, Jing Zhao 1, Dongchen Mao 1,2, Bo Li 1,2, Mingke Li 3,4

Affiliation(s)

1 School of Electronic Information, Xijing University, Xi'an, China
2 Henan Ruika Robot Manufacturing Co., LTD, Xinxiang, China; Shanghai Shuoka Robot Technology Co., LTD, Shanghai, China
3 Henan Ruika Robot Manufacturing Co., LTD, Xinxiang, China
4 Shanghai Shuoka Robot Technology Co., LTD, Shanghai, China

Corresponding Author

Anqi Wang

ABSTRACT

Hemorrhagic stroke is a serious cerebrovascular disease, which seriously endangers our life safety. Clinical intelligent diagnosis and treatment of hemorrhagic stroke, as a combination of artificial intelligence and intelligent medical treatment, is very conducive to improving the monitoring of patients' pathological cycle changes through data flow. Therefore, based on the BP neural network model, this paper is based on the personal medical history, medical history, morbidity and treatment history of 100 patients with hemorrhagic stroke, as well as patient prognosis assessment information. A neural network model based on GABP was constructed to successfully predict the 90-day mRS Score of patients, and provide recommendations for clinical decision-making according to the correlation between patient prognosis and personal history, medical history, treatment and imaging features. 

KEYWORDS

GABP, mRS, Prediction Model, Hemorrhagic stroke

CITE THIS PAPER

Anqi Wang, Jing Zhao, Dongchen Mao, Bo Li, Mingke Li, Climatic Factors Impact on Ultimate Frisbee: A Study on the Influence of Humidity and Temperature on Player Performance and Game Outcomes in Shanghai. MEDS Public Health and Preventive Medicine (2023) Vol. 3: 30-35. DOI: http://dx.doi.org/10.23977/phpm.2023.030605.

REFERENCES

[1] Wang Xiaoyan, Li Meizhou, Discussion on grade correlation coefficient and Spearman grade correlation coefficient, Journal of Guangdong Polytechnic of Light Industry, 2006, 4:26-27, 2006
[2] Qi Dehu, Kang Jichang. Design of BP neural network [J]. Computer Engineering and Design, 19 (2): 48-50,1998.
[3] Xuan Guangnan, Cheng Runwei, Genetic Algorithm and Engineering Optimization, China, Tsinghua University Press: 1-10, 2004
[4] Liu Xiufeng, Liu Fen. Classification of colorectal cancer syndrome by BP neural network based on genetic algorithm optimization [J]. Chinese Journal of Medical Library and Information, 27(3): 14-18, 2018. (in Chinese)
[5] Chongruksut W, Limpastan K, Jetjumnong C, et al. Age as a prognostic factor of 30-day mortality in hemorrhagic stroke patients: A Thai large tertiary care referral center[J]. Asian Journal of Surgery, 2020. DOI:10.1016/j.asjsur.2019.11.010.
[6] LIU Chunyan, LING Jianchun, KOU Linyuan. Performance comparison between GA-BP Neural Network and BP Neural Network [J]. Chinese Journal of Health Statistics,(2): 173-176, 2013.
[7] Fan Rong, Meng Dazhi, Xu Dashun, Research Progress of Statistical correlation analysis methods, Mathematical Modeling and Its Application, Vol. 3, No. 1:1-12, 2014
[8] Liang Xiaojun, Normality Test (3), Shanghai Statistics, 2000, 12:24-28
[9] Hu Qiong; Zhai,Xiaoyu; Li,Zhenfu, Multi-Objective Optimization of Deep-Sea Mining Pump Based on CFD, GABP Neural Network and NSGA-III Algorithm, Journal of Marine Science and Engineering, 2022,10:1063-1063

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 1922
Visits: 86386

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.