APA (7th ed.) Citation

MB, Y., C, T., BB, T., DG, D., K, F., ZD, A., . . . F, B. (2025). Artificial intelligence based predictive tools for identifying type 2 diabetes patients at high risk of treatment Non-adherence: A systematic review. International journal of medical informatics, 198, 105858. https://doi.org/10.1016/j.ijmedinf.2025.105858

Chicago Style (17th ed.) Citation

MB, Yismaw, et al. "Artificial Intelligence Based Predictive Tools for Identifying Type 2 Diabetes Patients at High Risk of Treatment Non-adherence: A Systematic Review." International Journal of Medical Informatics 198 (2025): 105858. https://doi.org/10.1016/j.ijmedinf.2025.105858.

MLA (9th ed.) Citation

MB, Yismaw, et al. "Artificial Intelligence Based Predictive Tools for Identifying Type 2 Diabetes Patients at High Risk of Treatment Non-adherence: A Systematic Review." International Journal of Medical Informatics, vol. 198, 2025, p. 105858, https://doi.org/10.1016/j.ijmedinf.2025.105858.