ArticleBMC bioinformatics2023
Causal discovery approach with reinforcement learning for risk factors of type II diabetes mellitus.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Optimizing hepatitis C diagnosis through reinforcement learning feature selection and multi-model machine learning evaluation.Scientific reports · 2026Article
- Causal Discovery in Observational Medical Research: Scoping Review.JMIR medical informatics · 2026Article
- Triplet offline causal discovery based on optimal Markov blanket and its application.Scientific reports · 2025Article
- Sensitivity analysis for causality in observational studies for regulatory science.Journal of clinical and translational science · 2023Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundStatistical correlation analysis is currently the most typically used approach for investigating the risk factors of type 2 diabetes mellitus (T2DM). However, this approach does not readily reveal the causal relationships between risk factors and rarely describes the causal relationships visually.
resultsConsidering the superiority of reinforcement learning in prediction, a causal discovery approach with reinforcement learning for T2DM risk factors is proposed herein. First, a reinforcement learning model is constructed for T2DM risk factors. Second, the process involved in the causal discovery method for T2DM risk factors is detailed. Finally, several experiments are designed based on diabetes datasets and used to verify the proposed approach.
conclusionsThe experimental results show that the proposed approach improves the accuracy of causality mining between T2DM risk factors and provides new evidence to researchers engaged in T2DM prevention and treatment research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.