Naito, T., Inoue, K., Namba, S., Sonehara, K., Suzuki, K., Matsuda, K., . . . Okada, Y. (2024). Machine learning reveals heterogeneous associations between environmental factors and cardiometabolic diseases across polygenic risk scores. Communications Medicine, 4(1), . https://doi.org/10.1038/s43856-024-00596-7
Chicago-referens (17:e uppl.)Naito, Tatsuhiko, et al. "Machine Learning Reveals Heterogeneous Associations Between Environmental Factors and Cardiometabolic Diseases Across Polygenic Risk Scores." Communications Medicine 4, no. 1 (2024). https://doi.org/10.1038/s43856-024-00596-7.
MLA-referens (9:e uppl.)Naito, Tatsuhiko, et al. "Machine Learning Reveals Heterogeneous Associations Between Environmental Factors and Cardiometabolic Diseases Across Polygenic Risk Scores." Communications Medicine, vol. 4, no. 1, 2024, https://doi.org/10.1038/s43856-024-00596-7.
