对于多个结果预测,找到有限数量的预测因子表型
Jenna M Reps1,2, Jenna Wong3, Egill A Fridgeirsson2
1Johnson & Johnson LLC, Raritan, New Jersey, USA jreps@its.jnj.com.
BMJ health & care informatics
|January 17, 2025
概括
研究人员确定了67个预测因素的核心集合,加上年龄和性别,可以用来构建多个预测模型. 这种方法简化了临床决策,通过在一个单一的网站形式上启用许多预测模型.
科学领域:
- 医疗信息学医学信息学
- 临床预测建模临床预测建模
- 生物统计学 生物统计学
背景情况:
- 预后模型对于医疗决策至关重要,但往往预测单个结果.
- 现有的模型需要独特的预测因素,限制了它们的综合使用.
- 需要一个统一的临床工具,从共同的预测器预测多个结果.
研究的目的:
- 识别一个受约束的,结果不可知的预测器集.
- 开发一种用于创建多功能预后模型的方法.
主要方法:
- 一种新的技术汇总了众多结果中的标准化平均差异.
- 该方法确定了与多个结果相关的受约束的预测指标集.
- 在8个预测任务中对各种基准进行了模型性能评估.
主要成果:
- 确定了一组受约束的67个预测因素,加上年龄和性别.
- 这些预测因素包括心血管,/肝,精神健康,胃肠道,传染病和瘤疾病.
- 使用受约束集的模型表现出比具有广泛预测因子的模型具有相似或略低的歧视性,优于现有的临床模型.
结论:
- 一个小而常见的预测器集可以支持许多结果的模型.
- 这便于通过单个接口实现多个预测模型.
- 已识别的预测器集作为未来预测模型研究的基础.
相关概念视频
01:49Multiple Allele Traits
34.0K
The Concept of Multiple Allelism
34.0K
01:18Polygenic Traits
64.7K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
64.7K
01:25Multiple Regression
2.9K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.9K
01:03Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
01:00Punnett Squares
112.5K
Overview
112.5K
01:19Survival Tree
57
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...
57