注射用血塞通不良反应风险评估系统：基于自动机器学习的设计

**摘要：**注射用血塞通是一种广泛应用于心脑血管疾病治疗的药物。然而，该药物也存在不良反应的风险。本文提出基于自动机器学习的注射用血塞通不良反应风险评估系统设计。首先，收集了大量的医疗数据，包括患者的基本信息、用药史以及不良反应记录等。然后，利用机器学习算法对数据进行分析和处理，得到注射用血塞通不良反应的相关特征。最后，设计了一个基于自动机器学习的注射用血塞通不良反应风险评估系统，该系统可以根据患者的个性化信息和历史记录，预测其注射用血塞通产生不良反应的概率，为医生提供更加科学的治疗建议。

**关键词：**注射用血塞通；不良反应；机器学习；风险评估

Abstract: Injection of xuesaitong is a widely used drug for the treatment of cardiovascular and cerebrovascular diseases. However, the drug also carries a risk of adverse reactions. This article proposes a design of an automatic machine learning-based risk assessment system for adverse reactions of injection of xuesaitong. Firstly, a large amount of medical data, including basic information of patients, medication history and adverse reaction records, were collected. Then, machine learning algorithms were used to analyze and process the data to obtain relevant features of adverse reactions of injection of xuesaitong. Finally, an automatic machine learning-based risk assessment system for adverse reactions of injection of xuesaitong was designed, which can predict the probability of adverse reactions of injection of xuesaitong based on the personalized information and historical records of patients, providing more scientific treatment advice for doctors.

Keywords: Injection of xuesaitong; Adverse reactions; Machine learning; Risk assessment.