Diabetes Risk Prediction Through Fine-Tuned Gradient Boosting
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56703-2_11
Reference19 articles.
1. Tasin, I., Nabil, T.U., Islam, S., Khan, R.: Diabetes prediction using machine learning and explainable AI techniques. Healthcare Technology Letters 10(1), 1–10 (2023). https://doi.org/10.1049/htl2.12039
2. Firdous, S., Wagai, G.A., Sharma, K.: A survey on diabetes risk prediction using machine learning approaches. J. Family Med. Prim. Care 11(11), 6929 (2022). https://doi.org/10.4103/jfmpc.jfmpc_502_22
3. Ahamed, B.S., Arya, M.S., Nancy, A.O.V.: Diabetes mellitus disease prediction using machine learning classifiers with oversampling and feature augmentation. Adv. Hum.-Comput. Interact. 22, 1–14 (2022). https://doi.org/10.1155/2022/9220560
4. Mujmdar, A., Vaidehi, V.: Diabetes prediction using machine learning algorithms. Procedia Comput. Sci. 165, 292–299 (2019)
5. Lamba, R., Gulati, T., Jain, A.: Automated Parkinson’s disease diagnosis system using transfer learning techniques. In: Marriwala, N., Tripathi, C.C., Jain, Shruti, Mathapathi, Shivakumar (eds.) Emergent Converging Technologies and Biomedical Systems: Select Proceedings of ETBS 2021, pp. 183–196. Springer Singapore, Singapore (2022). https://doi.org/10.1007/978-981-16-8774-7_16
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