You can also use the US Diabetes Surveillance System , an interactive web tool that provides diabetes data at national, state, and county levels and by age, sex, race/ethnicity, and education. The latest data on diabetes incidence, prevalence, complications, costs, and more.
Read moreHow do diabetics collect data?
Examples of quantitative data collection strategies include extracting data from existing sources, such as electronic health records or other clinical data, as well as conducting surveys or questionnaires, which can be administered by telephone, mail, or internet .
Read moreWhich classification algorithm performs better for diabetes dataset?
They found for better accuracy, Adaboost can be applied to predict diseases like diabetes, coronary heart disease, and hypertension. Sisodia et al. [18] found that, among the applied machine learning methods SVM, NB, and DT on PIDD, the NB classifier shows better accuracy at 76.30%.
Read moreWhat is the diabetes pedigree function?
DiabetesPedigreeFunction: Diabetes pedigree function (a function which scores likelihood of diabetes based on family history ) Age: Age (years) Outcome: Class variable (0 if non-diabetic, 1 if diabetic)
Read moreCan we predict diabetes?
Recently, numerous algorithms are used to predict diabetes , including the traditional machine learning method (Kavakiotis et al., 2017), such as support vector machine (SVM), decision tree (DT), logistic regression and so on.
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