构建训练集,使用时间序列数据的学习间距离图形模型对患者生理学的数据,以预测疾病得分
Dalia Chakrabarty1, Kangrui Wang2, Gargi Roy1
1Department of Mathematics, Brunel University London, Uxbridge, United Kingdom.
PloS one
|October 19, 2023
概括
这项研究引入了一种新的VOD-score,用于预测骨髓移植后的疾病易感性,从而能够更早地进行干预以改善生存率. 该得分利用患者的生理数据和图形理论进行可靠的风险评估.
科学领域:
- 计算生物学是一种计算生物学.
- 医疗信息学医学信息学
- 网络科学 网络科学
背景情况:
- 早期预测疾病易感性对于及时的医疗干预至关重要.
- 静脉封闭性疾病 (VOD) 是骨髓移植后的一种严重并发症,在这种情况下,存活与早期检测有关.
- 预测VOD风险的现有方法在准确性和范围上有局限性.
研究的目的:
- 开发和验证一种新的VOD-score,用于预测接受骨髓移植的患者的疾病易感性.
- 建立一种可靠的方法来量化个体患者的VOD风险.
- 通过提供VOD风险的定量衡量,促进早期干预策略.
主要方法:
- 利用了患者生理学上的时间序列数据,从移植前到移植后.
- 基于图形理论定义的VOD-score,特别是来自患者数据和参考数据的软随机几何图之间的距离.
- 采用矢量变量高斯过程和马尔科夫链蒙特卡洛推理来进行学习和预测.
主要成果:
- 成功地从回顾性队列数据中学习了VOD-score,与疾病易感性相关.
- 开发了一个预测模型,将VOD-score与移植前患者参数联系起来.
- 证明了VOD-score计算是可靠的,并且独立于数据长度.
结论:
- 开发的VOD-score提供了一种可靠的方法来预测骨髓移植后的VOD风险.
- 这种方法可以实现个性化的风险评估,并支持及时的临床决策.
- 这些发现为通过对VOD的早期干预为改善患者结果铺平了道路.
更多相关视频
相关概念视频
Survival Tree
88
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...
88
Prediction Intervals
2.3K
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.
2.3K
Classification of Illness
7.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.5K
Time-Series Graph
4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Residuals and Least-Squares Property
7.4K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.4K
End Point Prediction: Gran Plot
345
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
345


