Prediction of Diabetes Mellitus: Comparative Study of Various Machine Learning Models-Reference-Cited by-同舟云学术

Prediction of Diabetes Mellitus: Comparative Study of Various Machine Learning Models

Published:2020-07-31 Issue: Volume: Page:103-115
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Hussain Arooj,Naaz Sameena

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-15-5148-2_10

Reference34 articles.

1. S.N. Raina, A review on machine learning techniques. Int. J Recent Innov. Trends Comput. Commun. (2016). http://www.ijritcc.org. Accessed 04 Nov 2019

2. International Diabetes Federation, International diabetes federation—Complications. Idf.Org (2019). https://www.idf.org/aboutdiabetes/what-is-diabetes/complications.html. Accessed 04 Nov 2019

3. S. Naaz, Analysis of Mri images using data mining for detection of brain tumor. Int. J. Adv. Res. Comput. Sci. 9(2), 15–18 (2018)

4. K., S. Naaz, Machine learning algorithm to predict survivability in breast cancer patients. Int. J. Comput. Sci. Eng. 10(4), 97–101 (2018)

5. D. Hasan, Ki. Zehra, S. Naaz, H. Kaur, Classification Using 10 fold Cross Validation for Breast Cancer Prediction (2019)

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