| DiaHealth | R Documentation |
A Bangladeshi dataset for Type 2 diabetes prediction.
DiaHealth
A data frame with 5,437 patients and 14 variables on demographics, clinical parameters, and medical history.
ageYears (age of the person).
genderCategorical variable (Female, Male).
pulse_rateBeats per minute (bpm).
systolic_bpSBP in millimeters of mercury (mmHg).
diastolic_bpDBP (mmHg).
glucoseMilligrams per deciliter (mg/dL).
heightMeter (m).
weightKilogram (kg).
bmiBody mass index (BMI).
family_diabetesFamily history of diabetes.
hypertensiveHypertension.
family_hypertensionFamily history of hypertension.
cardiovascular_diseaseCVD.
strokeStroke.
diabeticDiabetic.
Key features include age, gender, pulse rate, blood pressure (systolic and diastolic), glucose level, BMI, and family history of diabetes and related conditions like hypertension and cardiovascular disease. The dataset is labeled with a binary outcome indicating whether each patient has diabetes. This rich dataset is designed to support the development and evaluation of machine learning models for diabetes detection, management, and treatment.
Prama TT, Zaman M, Sarker F, Mamun KA. (2024), “DiaHealth: A Bangladeshi Dataset for Type 2 Diabetes Prediction ”, Mendeley Data, V1, doi: 10.17632/7m7555vgrn.1
diabetes
data(DiaHealth)
knitr::kable(head(DiaHealth,5),caption="Five individauls in DiaHealth")
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