Diabetes Prediction Using Colab Notebook Based Machine Learning Methods
Öz
Anahtar Kelimeler
Kaynakça
- [1]Diabetes Overview, (2022). https://www.who.int/ne ws-room/fact-sheets/detail/diabetes
- [2]Diabetes, (2022). https://www.who.int/health-topics /diabetes#tab=tab_1
- [3]Güldoğan, E., Zeynep, T. U. N. Ç., Ayça, A. C. E. T., & ÇOLAK, C. (2020). Performance evaluation of different artificial neural network models in the classification of type 2 diabetes mellitus. The Journal of Cognitive Systems, 5(1), 23-32.
- [4]Maulidah, N., Abdilah, A., Nurlelah, E., Gata, W., & Hasan, F. N. (2020). Seleksi Fitur Klasifikasi Penyakit Diabetes Menggunakan Particle Swarm Optimization (PSO) Pada Algoritma Naive Bayes. Elkom: Jurnal Elektronika dan Komputer, 13(2), 40-48.
- [5]Tigga, N. P., & Garg, S. (2020). Prediction of type 2 diabetes using machine learning classification methods. Procedia Computer Science, 167, 706-716.
- [6]Jakka, A., & Vakula Rani, J. (2019). Performance evaluation of machine learning models for diabetes prediction. Int. J. Innov. Technol. Explor. Eng.(IJITEE), 8(11).
- [7]Sisodia, D., & Sisodia, D. S. (2018). Prediction of diabetes using classification algorithms. Procedia computer science, 132, 1578-1585.
- [8]Feng, T. C., Li, T. H. S., & Kuo, P. H. (2015). Variable coded hierarchical fuzzy classification model using DNA coding and evolutionary programming. Applied Mathematical Modelling, 39(23-24), 7401-7419.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Önder Yakut
*
0000-0003-0265-7252
Türkiye
Yayımlanma Tarihi
31 Mart 2023
Gönderilme Tarihi
7 Ekim 2022
Kabul Tarihi
16 Mart 2023
Yayımlandığı Sayı
Yıl 2023 Cilt: 9 Sayı: 1
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