End stage renal disease (ESRD) is the last stage of chronic kidney disease that requires dialysis or a kidney transplant to survive. Many studies reported a higher risk of mortality in ESRD patients compared with patients without ESRD. In this paper, we develop a model to predict postoperative complications, major cardiac event, for patients who underwent any type of surgery. We compare several widely-used machine learning models through experiments with our collected data yellow of size 3220, and achieved F1 score of 0.797 with the random forest model. Based on experimental results, we found that features related to operation (e.g., anesthesia time, operation time, crystal, and colloid) have the biggest impact on model performance, and also found the best combination of features. We believe that this study will allow physicians to provide more appropriate therapy to the ESRD patients by providing information on potential postoperative complications.

中文翻译：

---

末期肾病患者术后并发症的预测

终末期肾脏疾病（ESRD）是需要透析或进行肾脏移植才能生存的慢性肾脏疾病的最后一个阶段。许多研究报告说，与没有ESRD的患者相比，ESRD患者的死亡风险更高。在本文中，我们开发了一种模型，用于预测接受任何类型手术的患者的术后并发症，主要心脏事件。我们通过实验比较了几种广泛使用的机器学习模型，我们收集的数据黄色为3220，并且使用随机森林模型获得的F1分数为0.797。根据实验结果，我们发现与操作相关的功能（例如麻醉时间，操作时间，晶体和胶体）对模型性能的影响最大，并且找到了功能的最佳组合。