scholarly journals Comparative Analysis of Data Mining Classification Algorithms in Type-2 Diabetes Prediction Data Using WEKA Approach

2014 ◽  
Vol 7 (2) ◽  
Author(s):  
Kawsar Ahmed ◽  
Tasnuba Jesmin
Keyword(s):  
Data Mining ◽  
Type 2 Diabetes ◽  
Comparative Analysis ◽  
Classification Algorithms ◽  
Diabetes Prediction

scholarly journals Comparative analysis of classification models for diagnosis Type 2 Diabetes

2021 ◽  
Author(s):  
Daniah Almadni
Keyword(s):  
Data Mining ◽  
Type 2 Diabetes ◽  
Comparative Analysis ◽  
Expert System ◽  
Support Vector ◽  
Fuzzy Expert System ◽  
Inference System ◽  
Data Mining Algorithms ◽  
Mining Algorithms

Diabetes mellitus type 2 has become one of the major causes of premature diseases and death in many countries. It accounts for the majority of diabetes cases around the world. Thus, we need to develop a system that diagnoses type 2 diabetes. In this thesis, a fuzzy expert system is proposed using the Mamdani fuzzy inference system to diagnose type 2 diabetes effectively. In order to evaluate the performance of our system, a comparative study has been initiated, and will contrast the proposed system with data mining algorithms, namely J48 Decision tree, multilayer perceptron, support vector machine, and Naïve Bayes. The developed fuzzy expert system and the data mining algorithms are validated with real data from the UCI machine learning datasets. Moreover, the performance of the fuzzy expert system is evaluated by comparing it to related work that used the Mamdani inference system to diagnose the incidence of type 2 diabetes. Alternate title: Comparative analysis of data mining algorithms for diagnosis Type 2 Diabetes

scholarly journals Comparative analysis of classification models for diagnosis Type 2 Diabetes

2021 ◽  
Author(s):  
Daniah Almadni
Keyword(s):  
Data Mining ◽  
Type 2 Diabetes ◽  
Comparative Analysis ◽  
Expert System ◽  
Support Vector ◽  
Fuzzy Expert System ◽  
Inference System ◽  
Data Mining Algorithms ◽  
Mining Algorithms

Diabetes mellitus type 2 has become one of the major causes of premature diseases and death in many countries. It accounts for the majority of diabetes cases around the world. Thus, we need to develop a system that diagnoses type 2 diabetes. In this thesis, a fuzzy expert system is proposed using the Mamdani fuzzy inference system to diagnose type 2 diabetes effectively. In order to evaluate the performance of our system, a comparative study has been initiated, and will contrast the proposed system with data mining algorithms, namely J48 Decision tree, multilayer perceptron, support vector machine, and Naïve Bayes. The developed fuzzy expert system and the data mining algorithms are validated with real data from the UCI machine learning datasets. Moreover, the performance of the fuzzy expert system is evaluated by comparing it to related work that used the Mamdani inference system to diagnose the incidence of type 2 diabetes. Alternate title: Comparative analysis of data mining algorithms for diagnosis Type 2 Diabetes

COMPARATIVE ANALYSIS OF USING VARIOUS SCHEMES OF TREATMENT OF PATIENTS WITH POSTINFARCTION CARDIOSCLEROSIS AND TYPE 2 DIABETES

2015 ◽  
pp. 7-14
Author(s):  
O. M. Bilovol ◽  
◽  
P. G. Kravchun ◽  
N. G. Ryndina ◽  
P. I. Rynchak ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Comparative Analysis ◽  
Postinfarction Cardiosclerosis

Use of Data Mining in the prediction of risk factors of Type 2 diabetes mellitus in Gulf countries

2021 ◽  
Vol 8 (4) ◽  
pp. 638-645
Author(s):  
W. Boutayeb ◽  
◽  
M. Badaoui ◽  
H. Al Ali ◽  
A. Boutayeb ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Gulf Coast ◽  
Use Of Data ◽  
Gulf Countries ◽  
Unhealthy Diet

Prevalence of diabetes in Gulf countries is knowing a significant increase because of various risk factors, such as: obesity, unhealthy diet, physical inactivity and smoking. The aim of our proposed study is to use Data Mining and Data Analysis tools in order to determine different risk factors of the development of Type~2 diabetes mellitus (T2DM) in Gulf countries, from Gulf COAST dataset.

scholarly journals High saturated-fat and low-fibre intake: a comparative analysis of nutrient intake in individuals with and without type 2 diabetes

2014 ◽  
Vol 4 (2) ◽  
pp. e104-e104 ◽  
Author(s):  
C Breen ◽  
M Ryan ◽  
B McNulty ◽  
M J Gibney ◽  
R Canavan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Comparative Analysis ◽  
Nutrient Intake ◽  
Saturated Fat ◽  
Fibre Intake

scholarly journals Comparative analysis of risk for falls in patients with and without type 2 diabetes mellitus

2012 ◽  
Vol 58 (2) ◽  
pp. 234-239 ◽  
Author(s):  
Patricia Pereira de Oliveira ◽  
Silvia Maria Fachin ◽  
Joana Tozatti ◽  
Mari Cassol Ferreira ◽  
Lizanka Paola Figueiredo Marinheiro
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Comparative Analysis
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