Classification of DNA Sequence for Diabetes Mellitus Type Using Machine Learning Methods
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9562-2_8
Reference38 articles.
1. Li X, Zhang J, Safara F (2023) Improving the accuracy of diabetes diagnosis applications through a hybrid feature selection algorithm. Neural Process Lett 55(1). https://doi.org/10.1007/s11063-021-10491-0
2. Arora A, Shoeibi N, Sati V, González-Briones A, Chamoso P, Corchado E (2021) Data augmentation using Gaussian mixture model on csv files. Adv Intell Syst Comput. https://doi.org/10.1007/978-3-030-53036-5_28
3. Mirza S, Mittal S, Zaman M (2018) Decision support predictive model for prognosis of diabetes using SMOTE and decision tree
4. Bubby S, Chrisman B (2021) DNA-SEnet: a convolutional neural network for classifying DNA-asthma associations. J Emerg Investig 4
5. Lugo L, Hernández EB (2021) A recurrent neural network approach for whole genome bacteria identification. Appl Artif Intell 35(9):642–656. https://doi.org/10.1080/08839514.2021.1922842
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