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 in the MESA Study. Circulation .147(2):132-141. -Simultaneous publication at AHA Scientific Session 2023-
    • 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.52(4):1243-1256.
    • Inoue K, Watson KE, Kondo N, Horwich T, Hsu W, Bui A, Duru OK. (2022). Association of Intensive Blood Pressure Control and Living Arrangement on Cardiovascular Outcomes by Race. JAMA Network Open; 1;5(3):e222037
    • Prosper A, Inoue K (co-first), Kathleen B, Bui A, Aberle D, Hsu W. (2021). Association of Inclusion of More Black Individuals in Lung Cancer Screening With Reduced Mortality. JAMA Network Open: 4(8), e2119629-e2119629.
    • Inoue K*, Athey S, Baicker K, Tsugawa Y. (2024) Heterogeneous effects of Medicaid coverage on cardiovascular risk factors: secondary analysis of randomized controlled trial. BMJ . 386: e079377.
    • Inoue K*, Adomi M, Efthimiou O, Komura T, Omae K, Onishi A, Tsutsumi Y, Fujii T, Kondo N, Furukawa AT. (2024) Machine Learning Approaches to Evaluate Heterogeneous Treatment Effects in Randomized Controlled Trials: A Scoping Review. J Clin Epidemiol. (Online ahead of print)
    • Naito T, Inoue K* (co-first). (2024) A machine learning approach reveals heterogeneous association of environmental factors with diseases across polygenic risk scores: an application to cardiovascular diseases and type 2 diabetes. Communications Medicine. (In press)
    • Kiyohara K, Kondo N, Iwami T, Yano Y, Nishiyama A, Node K, Inagaki N, Duru KO, Inoue K* (2024) Heterogeneous Effects of Intensive Glycemic and Blood Pressure on Cardiovascular Events among Diabetes by Living Arrangements. Journal of American Heart Association. 13(13):e033860.
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