南方科技大学知识苑(SUSTech KC): Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features

题名	Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features
作者	Lin, Xiaoxuan 1; Chen, Lixin 1; Zhang, Defu 1; Luo, Shuyu 1; Sheng, Yuanyuan 1; Liu, Xiaohua 1; Liu, Qian 1; Li, Jian 1; Shi, Bobo 1; Peng, Guijuan 1; Zhong, Xiaofang 1; Huang, Yuxiang 1; Li, Dagang 2,3; Qin, Gengliang 2,3; Yin, Zhiqiang 2,3; Xu, Jinfeng 1; Meng, Chunying 2,3; Liu, Yingying 1
通讯作者	Xu, Jinfeng; Meng, Chunying; Liu, Yingying
发表日期	2023-02-01
DOI	10.3390/jcm12031193
发表期刊	JOURNAL OF CLINICAL MEDICINE 影响因子和分区
EISSN	2077-0383
卷号	12 期号:3
摘要	In this study, we aimed to develop a prediction model to assist surgeons in choosing an appropriate surgical approach for mitral valve disease patients. We retrospectively analyzed a total of 143 patients who underwent surgery for mitral valve disease. The XGBoost algorithm was used to establish a predictive model to decide a surgical approach (mitral valve repair or replacement) based on the echocardiographic features of the mitral valve apparatus, such as leaflets, the annulus, and sub-valvular structures. The results showed that the accuracy of the predictive model was 81.09% in predicting the appropriate surgical approach based on the patient's preoperative echocardiography. The result of the predictive model was superior to the traditional complexity score (81.09% vs. 75%). Additionally, the predictive model showed that the three main factors affecting the choice of surgical approach were leaflet restriction, calcification of the leaflet, and perforation or cleft of the leaflet. We developed a novel predictive model using the XGBoost algorithm based on echocardiographic features to assist surgeons in choosing an appropriate surgical approach for patients with mitral valve disease.
关键词	mitral valve disease echocardiography prediction XGBoost mitral valve repair mitral valve replacement
相关链接	[来源记录]
收录类别	SCI
语种	英语
学校署名	通讯
WOS研究方向	General & Internal Medicine
WOS类目	Medicine, General & Internal
WOS记录号	WOS:000931072000001
出版者	MDPI
来源库	Web of Science
引用统计	被引频次[WOS]：2
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/501444
专题	南方科技大学第一附属医院
作者单位	1.Jinan Univ, Shenzhen Peoples Hosp, Clin Med Coll 2, Dept Ultrasound, Shenzhen 518020, Peoples R China 2.Jinan Univ, Shenzhen Peoples Hosp, Dept Cardiovasc Surg, Clin Med Coll 2, Shenzhen 518020, Peoples R China 3.Southern Univ Sci & Technol, Affiliated Hosp 1, Shenzhen 518020, Peoples R China
通讯作者单位	南方科技大学第一附属医院
推荐引用方式 GB/T 7714	Lin, Xiaoxuan,Chen, Lixin,Zhang, Defu,et al. Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features[J]. JOURNAL OF CLINICAL MEDICINE,2023,12(3).
APA	Lin, Xiaoxuan.,Chen, Lixin.,Zhang, Defu.,Luo, Shuyu.,Sheng, Yuanyuan.,...&Liu, Yingying.(2023).Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features.JOURNAL OF CLINICAL MEDICINE,12(3).
MLA	Lin, Xiaoxuan,et al."Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features".JOURNAL OF CLINICAL MEDICINE 12.3(2023).