Prognostic study of hemorrhagic stroke patients based on GABP neural network model
DOI: 10.23977/phpm.2023.030605 | Downloads: 11 | Views: 541
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 WangABSTRACT
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 strokeCITE 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.
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