TY - JOUR AU - Fan, Jiaxin AU - Chen, Mengying AU - Luo, Jian AU - Yang, Shusen AU - Shi, Jinming AU - Yao, Qingling AU - Zhang, Xiaodong AU - Du, Shuang AU - Qu, Huiyang AU - Cheng, Yuxuan AU - Ma, Shuyin AU - Zhang, Meijuan AU - Xu, Xi AU - Wang, Qian AU - Zhan, Shuqin PY - 2021 DA - 2021/04/05 TI - The prediction of asymptomatic carotid atherosclerosis with electronic health records: a comparative study of six machine learning models JO - BMC Medical Informatics and Decision Making SP - 115 VL - 21 IS - 1 AB - Screening carotid B-mode ultrasonography is a frequently used method to detect subjects with carotid atherosclerosis (CAS). Due to the asymptomatic progression of most CAS patients, early identification is challenging for clinicians, and it may trigger ischemic stroke. Recently, machine learning has shown a strong ability to classify data and a potential for prediction in the medical field. The combined use of machine learning and the electronic health records of patients could provide clinicians with a more convenient and precise method to identify asymptomatic CAS. SN - 1472-6947 UR - https://doi.org/10.1186/s12911-021-01480-3 DO - 10.1186/s12911-021-01480-3 ID - Fan2021 ER -