Heterogeneous Treatment Effect Estimation with Subpopulation Identification for Personalized Medicine in Opioid Use
Seungyeon Lee1,2, Ruoqi Liu1,2, Wenyu Song3
1Department of Computer Science and Engineering, The Ohio State University, USA.
Proceedings. IEEE International Conference on Data Mining
|February 23, 2024
Summary
This study introduces SubgroupTE, a deep learning framework for personalized treatment effect estimation. It identifies patient subgroups and estimates tailored treatment effects, improving accuracy for diverse populations.
Area of Science:
- Artificial Intelligence
- Biomedical Informatics
- Machine Learning
Background:
- Deep learning models show promise for estimating treatment effects (TEE).
- Existing models often fail to account for outcome variations across patient subgroups.
- This oversight limits personalized treatment recommendations.
Purpose of the Study:
- To introduce SubgroupTE, a novel neural network framework for subgroup identification and treatment effect estimation.
- To improve the accuracy of treatment effect estimation by addressing heterogeneity in treatment responses.
- To enhance personalized treatment recommendations for specific patient groups.
Main Methods:
- Developed a neural network-based framework, SubgroupTE.
- Integrated subgroup identification with simultaneous treatment effect estimation.
- Evaluated performance on synthetic and real-world datasets.
Main Results:
- SubgroupTE demonstrated superior performance in treatment effect estimation compared to existing models on synthetic data.
- Experiments on an opioid use disorder (OUD) dataset showed SubgroupTE's potential for personalized recommendations.
- The model effectively identifies subgroups and estimates heterogeneous treatment effects.
Conclusions:
- SubgroupTE offers an improved approach to estimating treatment effects by considering subgroup heterogeneity.
- The framework has significant potential for developing personalized treatment strategies, particularly in complex conditions like OUD.
- This work advances the application of AI in precision medicine.
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