Machine Learning-Based Diabetes Prediction Using Missing Value Impotency
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-8739-6_51
Reference21 articles.
1. Khanam, J.J., Foo, S.Y.: A comparison of machine learning algorithms for diabetes prediction. ICT Express (2021). https://doi.org/10.1016/j.icte.2021.02.004
2. Ghaderi, M., Farahani, M.A., Hajiha, N., Ghaffari, F., Haghani, H.: The role of smartphone-based education on the risk perception of type 2 diabetes in women with gestational diabetes. Health Technol. (Berl) 9(5), 829–837 (2019). https://doi.org/10.1007/s12553-019-00342-3
3. Mandal, S.: New molecular biomarkers in precise diagnosis and therapy of Type 2 diabetes. Health Technol. (Berl) 10(3), 601–608 (2020). https://doi.org/10.1007/s12553-019-00385-6
4. Himsworth, H.P.: The syndrome of diabetes mellitus and its causes. Lancet 253(6551), 465–473 (1949). https://doi.org/10.1016/S0140-6736(49)90797-7
5. Mujumdar, A., Vaidehi, V.: Diabetes prediction using machine learning algorithms. Procedia Comput. Sci. 165, 292–299 (2019). https://doi.org/10.1016/j.procs.2020.01.047
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