Next Article in Journal
Managing News Overload (MNO): The COVID-19 Infodemic
Previous Article in Journal
Analysis of the Awareness and Popularity of the Brand of a Selected Education and Research Library in the Czech Republic: A Case Study
Open AccessArticle

Evaluating Machine Learning Methods for Predicting Diabetes among Female Patients in Bangladesh

Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh
*
Author to whom correspondence should be addressed.
Information 2020, 11(8), 374; https://doi.org/10.3390/info11080374
Received: 19 June 2020 / Revised: 19 July 2020 / Accepted: 20 July 2020 / Published: 23 July 2020
Machine Learning has a significant impact on different aspects of science and technology including that of medical researches and life sciences. Diabetes Mellitus, more commonly known as diabetes, is a chronic disease that involves abnormally high levels of glucose sugar in blood cells and the usage of insulin in the human body. This article has focused on analyzing diabetes patients as well as detection of diabetes using different Machine Learning techniques to build up a model with a few dependencies based on the PIMA dataset. The model has been tested on an unseen portion of PIMA and also on the dataset collected from Kurmitola General Hospital, Dhaka, Bangladesh. The research is conducted to demonstrate the performance of several classifiers trained on a particular country’s diabetes dataset and tested on patients from a different country. We have evaluated decision tree, K-nearest neighbor, random forest, and Naïve Bayes in this research and the results show that both random forest and Naïve Bayes classifier performed well on both datasets. View Full-Text
Keywords: diabetes prediction; PIMA dataset; Kurmitola general hospital; machine learning; classification diabetes prediction; PIMA dataset; Kurmitola general hospital; machine learning; classification
Show Figures

Figure 1

MDPI and ACS Style

Pranto, B.; Mehnaz, S.M.; Mahid, E.B.; Sadman, I.M.; Rahman, A.; Momen, S. Evaluating Machine Learning Methods for Predicting Diabetes among Female Patients in Bangladesh. Information 2020, 11, 374. https://doi.org/10.3390/info11080374

AMA Style

Pranto B, Mehnaz SM, Mahid EB, Sadman IM, Rahman A, Momen S. Evaluating Machine Learning Methods for Predicting Diabetes among Female Patients in Bangladesh. Information. 2020; 11(8):374. https://doi.org/10.3390/info11080374

Chicago/Turabian Style

Pranto, Badiuzzaman; Mehnaz, Sk. M.; Mahid, Esha B.; Sadman, Imran M.; Rahman, Ahsanur; Momen, Sifat. 2020. "Evaluating Machine Learning Methods for Predicting Diabetes among Female Patients in Bangladesh" Information 11, no. 8: 374. https://doi.org/10.3390/info11080374

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop