A review on longitudinal data analysis with random forest in precision medicine

@article{Hu2022ARO,
  title={A review on longitudinal data analysis with random forest in precision medicine},
  author={Jianchang Hu and Silke Szymczak},
  journal={Briefings in bioinformatics},
  year={2022}
}
In longitudinal studies variables are measured repeatedly over time, leading to clustered and correlated observations. If the goal of the study is to develop prediction models, machine learning approaches such as the powerful random forest (RF) are often promising alternatives to standard statistical methods, especially in the context of high-dimensional data. In this paper, we review extensions of the standard RF method for the purpose of longitudinal data analysis. Extension methods are… 
[PDF] Semantic Reader
1 Citations
Methods Citations
1

Figures and Tables from this paper

One Citation

Machine Learning Applications in Healthcare

  • VanshikaNeetu Gupta
  • Medicine, Computer Science
    2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)
  • 2022
This study examines numerous applications in the medical sciences of machine learning, a branch of artificial intelligence, and finds support vector algorithms and neural networks may be even more effective than the methods now employed in medicine.

References

SHOWING 1-10 OF 54 REFERENCES

Classification of repeated measurements data using tree-based ensemble methods

The proposal is an improvement of adhoc strategies and of the use all measurements of each subject or block strategy and the performance of the proposed methods with bagged classification trees (bagging) and random forests in the situation of longitudinal data is investigated.

Random forests for high-dimensional longitudinal data

A new method which takes intra-individual covariance into consideration to build random forests for high-dimensional longitudinal data is introduced and applied to an HIV vaccine trial including 17 HIV-infected patients with 10 repeated measurements of 20,000 gene transcripts and blood concentration of human immunodeficiency virus RNA.

Tree-Structured Methods for Longitudinal Data

Abstract The thrust of tree techniques is the extraction of meaningful subgroups characterized by common covariate values and homogeneous outcome. For longitudinal data, this homogeneity can pertain…

Random-effects models for longitudinal data.

A unified approach to fitting these models, based on a combination of empirical Bayes and maximum likelihood estimation of model parameters and using the EM algorithm, is discussed.

Evaluation of variable selection methods for random forests and omics data sets

Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees

The generalized linear mixed-effects model tree (GLMM tree) algorithm is proposed, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset.

Binary partitioning for continuous longitudinal data: categorizing a prognostic variable

A binary partitioning algorithm based on the use of the likelihood ratio statistic to evaluate the performance of individual splits based on an optimal split of a continuous prognostic variable is investigated.

Ensemble classification of paired data

Applied Longitudinal Analysis

dents and as a reference for those researchers embarking on running their own designed experiment, provides thorough coverage of a wide variety of topics for a number of experimental situations. The…

Fifty Years of Classification and Regression Trees

This article surveys the developments and briefly reviews the key ideas behind some of the major algorithms in regression tree algorithms.
...