1. 1) Kavakiotis I, Tsave O, Salifoglou A, Maglaveras N, Vlahavas I, Chouvarda I. Machine learning and data mining methods in diabetes research. Comput. Struct. Biotechnol. J., 15, 104–116 (2017).
2. 2) French MN, Krajewski WF, Cuykendall RR. Rainfall forecasting in space and time using a neural network. J. Hydrol., 137, 1–31 (1992).
3. 3) Imai S, Yamada T, Kasashi K, Kobayashi M, Iseki K. Usefulness of a decision tree model for the analysis of adverse drug reactions: evaluation of a risk prediction model of vancomycin-associated nephrotoxicity constructed using a data mining procedure. J. Eval. Clin. Pract., 23, 1240–1246 (2017).
4. 4) Imai S, Yamada T, Kasashi K, Ishiguro N, Kobayashi M, Iseki K. Construction of a flow chart-like risk prediction model of ganciclovir-induced neutropaenia including severity grade: a data mining approach using decision tree. J. Clin. Pharm. Ther., 44, 726–734 (2019).
5. 5) Yasuhara M, Iga T, Zenda H, Okumura K, Oguma T, Yano Y, Hori R. Population pharmacokinetics of vancomycin in Japanese adult patients. Ther. Drug Monit., 20, 139–148 (1998).