Research
General research interest
Causal Inference and Machine Learning in Chronic Disease Epidemiology
Major research interest
- Identifying mechanisms (causal mediation analysis, marginal structural model, front-door formula, etc)
- Identifying heterogeneity (causal forest, subgroup analysis, etc)
- Generalizing/Transporting the results
Research lists
- Methodology/Biasesimageupdate on 13/12/2022
Methodology/Biases
Inoue K, Ritz B, Arah OA. (2022). Causal Effect of Chronic Pain on Mortality through Opioid prescriptions: An Application of the Front-Door Formula. Epidemiology;33(4):572-580 Inoue K, Haseda ... - Machine Learningimageupdate on 13/12/2022
Machine Learning
Inoue K, Athey S, Tsugawa Y. (2023). Machine-learning-based high-benefit approach versus conventional high-risk approach in blood pressure management. International Journal of Epidemiology. In p... - Generalizing/Transporting the resultsimageupdate on 24/03/2022
Generalizing/Transporting the results
Inoue K, Hsu W, Arah OA, Prosper A, Aberle D, Bui A. (2021). Generalizability and transportability of the results from randomized controlled trials: An example using the National Lung Screening ... - Identifying heterogeneityimageupdate on 24/03/2022
Identifying heterogeneity
Inoue K, Seeman T, Horwich T, Budoff M, Watson KE (2022). Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine Learning Approach ... - Identifying mechanismsimageupdate on 24/03/2022
Identifying mechanisms
<Causal Mediation Analysis> Inoue K, Goldwater D, Allison M, Seeman T, Watson K. (2020). Serum Aldosterone Concentration, Coronary Artery Calcium, and Mortality: The Multi-Ethnic Study of...
