scholarly journals Polyneuropathy disease forecast in the type 2 diabetes mellitus patients using data mining based approach

2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Nur Kuban Torun
Keyword(s):  
Diabetes Mellitus ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Disease Forecast ◽  
Using Data

scholarly journals Risk Assessment of Sarcopenia in Patients With Type 2 Diabetes Mellitus Using Data Mining Methods

2020 ◽  
Vol 11 ◽  
Author(s):  
Mengzhao Cui ◽  
Xiaokun Gang ◽  
Fang Gao ◽  
Gang Wang ◽  
Xianchao Xiao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Type 2 Diabetes Mellitus ◽  
Mining Methods ◽  
Using Data

scholarly journals Comorbidity Study on Type 2 Diabetes Mellitus Using Data Mining

2012 ◽  
Vol 27 (2) ◽  
pp. 197 ◽  
Author(s):  
Hye Soon Kim ◽  
A Mi Shin ◽  
Mi Kyung Kim ◽  
Yoon Nyun Kim
Keyword(s):  
Diabetes Mellitus ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Using Data

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.

Socioeconomic Correlates of Inpatient Spending for Patients with Type 2 Diabetes Mellitus in China: Evidence from Hangzhou

2012 ◽  
Vol 120 (01) ◽  
pp. 35-44 ◽  
Author(s):  
H. Li ◽  
B. Chen ◽  
N. Shah ◽  
Z. Wang ◽  
K. Eggleston
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Insurance Coverage ◽  
Cost Effective ◽  
Patient Characteristics ◽  
Artery Disease ◽  
Using Data ◽  
Pharmaceutical Costs

AbstractWe evaluated the factors associated with inpatient costs including total costs, pharmaceutical costs and laboratory costs for diabetes-related admissions.Using data for 960 adult patients admitted between May 2005 and April 2008 with a primary or secondary diagnosis of type 2 diabetes mellitus (DM) at Sir Run Run Shaw Hospital affiliated with Zhejiang University Medical School (SRRSH) in Hangzhou, China, we evaluate the association between patient characteristics and inpatient costs with multivariable regression analyses.Total inpatient costs were positively associated with age, higher UKPDS stroke risk score, and presence of any complication. A regression that included patient socioeconomic and clinical characteristics explained 21.5% of the variation in total inpatient costs; regression estimates indicate that patients with coronary artery disease, retinopathy, nephropathy, neuropathy, and diabetic foot had inpatient costs that were respectively 93.7%, 14.0%, 17.5%, 11.5% and 89.0% higher than otherwise similar patients without those complications. Pharmaceutical costs did not differ by insurance coverage. Insured patients spent 7–16% more on laboratory tests than otherwise similar patients did.Clinical factors, especially presence of diabetes-related complications, appear to be the primary determinants of variation in inpatient costs for patients with type 2 DM in China. To mitigate the health costs increases associated with China’s DM epidemic, policymakers should focus on cost-effective ways to manage patients in outpatient settings to prevent the complications associated with diabetes.

scholarly journals Type 2 diabetes mellitus prediction model based on data mining

2018 ◽  
Vol 10 ◽  
pp. 100-107 ◽  
Author(s):  
Han Wu ◽  
Shengqi Yang ◽  
Zhangqin Huang ◽  
Jian He ◽  
Xiaoyi Wang
Keyword(s):  
Diabetes Mellitus ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Prediction Model ◽  
Model Based
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