竞争风险事件发生时间的预测：克罗恩病手术并发症的病例研究
Ensemble Prediction of Time to Event Outcomes with Competing Risks: A Case Study of Surgical Complications in Crohn's Disease
摘要：
我们开发了一种新的算法来预测克罗恩病诊断后5年内腹部大手术的发生，使用瑞典人口登记的29个基线协变量。我们基于Aalen-Johansen估计量的原因特定的累积发病率与现代机器学习方法的合奏伪观测模型。伪观测预处理可以轻松地将所有现有或新的机器学习过程扩展到右删失事件历史数据。我们提出了基于伪观测的估计的面积下的时变ROC曲线，优化合奏，和预测曲线，评估和总结预测性能。
英文摘要：
We develop a novel algorithm to predict the occurrence of major abdominal surgery within 5 years following Crohn's disease diagnosis using a panel of 29 baseline covariates from the Swedish population registers. We model pseudo-observations based on the Aalen-Johansen estimator of the cause-specific cumulative incidence with an ensemble of modern machine learning approaches. Pseudo-observation pre-processing easily extends all existing or new machine learning procedures to right-censored event history data. We propose pseudo-observation based estimators for the area under the time varying ROC curve, for optimizing the ensemble, and the predictiveness curve, for evaluating and summarizing predictive performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
