Machine Learning approach for Diabetes Prediction using Pima Dataset

Author:

Moon Pradnya Sumit1ORCID,Bainalwar Prachi A.2ORCID,Borkar Shubhangi M.1ORCID,Shambharkar Shubhangii S.3ORCID

Affiliation:

1. Computer Technology, Yeshwantrao Chavan College of Engineering, India

2. Yeshwantrao Chavan College of Engineering, Nagpur, India

3. Computer Technology, Yeshwantrao Chavhan College of Engineering, India

Publisher

ACM

Reference30 articles.

1. A deep learning approach using effective preprocessing techniques to detect covid-19 from chest CT-scan and X-ray images;Ahamed K. U.;Computers in Biology and Medicine, 139, Article,2021

2. Type 2 Machine Learning: An Effective Hybrid Prediction Model for Early Type 2 Diabetes Detection

3. Khetani, V. ., Gandhi, Y. ., Bhattacharya, S. ., Ajani, S. N. ., & Limkar, S. . (2023). Cross-Domain Analysis of ML and DL: Evaluating their Impact in Diverse Domains. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 253–262. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2951

4. Choubey, D.K., Paul, S., Kumar, S., Kumar, S., 2017. Classification of Pima indian diabetes dataset using naive bayes with genetic algorithm as an attribute selection, in: Communication and Computing Systems: Proceedings of the International Conference on Communication and Computing System (ICCCS 2016), pp. 451– 455.

5. DLMBHCO: design of an augmented bioinspired deep learning-based multidomain body parameter analysis via heterogeneous correlative body organ analysis

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