超越NLL:对歧视性和校准事件时间生存预测的路径交叉损失.
IEEE journal of biomedical and health informatics
|January 6, 2026
概括
路径交叉 (PCE) 通过直接学习事件轨迹来改进深度生存模型. 这个新的目标提高了预测准确度和校准,超过了传统的负日志概率方法.
科学领域:
- 机器学习 机器学习
- 生物统计学 生物统计学
- 计算生物学 计算生物学
背景情况:
- 深度生存模型对于时间到事件预测至关重要,但像负日志概率 (NLL) 这样的训练目标存在局限性.
- NLL可能会导致时间失衡和梯度问题,导致校准不佳,特别是在审查和竞争风险的情况下.
研究的目的:
- 引入路径交叉 (PCE) 作为深度生存模型的高级培训目标.
- 解决NLL在处理审查,竞争风险和时间信息不平衡方面的局限性.
主要方法:
- 开发了Pathwise Cross-Entropy (PCE),一个对称的,全路客观学习的累积发病率函数 (CIF).
- 对竞争风险进行扩展的PCE,采用因果特定监督,以避免多项性合.
- 在SEER和脏数据集上使用各种骨干评估PCE.
主要成果:
- 与NLL相比,PCE持续改善了歧视 (C指数,AUC) 和校准 (IBS).
- PCE产生了更准确的校准图表 (ECE,PP图表).
- 通过PCE,可以在最小的单调性违规的情况下直接预测顺序式的首次击中时间.
结论:
- PCE是单一和竞争风险生存分析的可靠和可解释的培训目标.
- 对于时间到事件的预测,PCE的直接CIF学习方法比NLL提供了显著的优势.
- 在深度生存模型中,PCE提高了预测性能和可解释性.
相关概念视频
Censoring Survival Data
518
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
518
Survival Tree
382
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
382
Kaplan-Meier Approach
556
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
556
Comparing the Survival Analysis of Two or More Groups
548
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
548
Introduction To Survival Analysis
738
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
738
Truncation in Survival Analysis
571
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
571


