DiaHealth

A Bangladeshi dataset for Type 2 diabetes prediction.

Usage

DiaHealth

Format

A data frame with 5,437 patients and 14 variables on demographics, clinical parameters, and medical history.

age

Years (age of the person).

gender

Categorical variable (Female, Male).

pulse_rate

Beats per minute (bpm).

systolic_bp

SBP in millimeters of mercury (mmHg).

diastolic_bp

DBP (mmHg).

glucose

Milligrams per deciliter (mg/dL).

height

Meter (m).

weight

Kilogram (kg).

bmi

Body mass index (BMI).

family_diabetes

Family history of diabetes.

hypertensive

Hypertension.

family_hypertension

Family history of hypertension.

cardiovascular_disease

CVD.

stroke

Stroke.

diabetic

Diabetic.

Source

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

Details

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.

See also

diabetes

Examples

data(DiaHealth)
knitr::kable(head(DiaHealth,5),caption="Five individauls in DiaHealth")
#> 
#> 
#> Table: Five individauls in DiaHealth
#> 
#> | age|gender | pulse_rate| systolic_bp| diastolic_bp| glucose| height| weight|   bmi| family_diabetes| hypertensive| family_hypertension| cardiovascular_disease| stroke|diabetic |
#> |---:|:------|----------:|-----------:|------------:|-------:|------:|------:|-----:|---------------:|------------:|-------------------:|----------------------:|------:|:--------|
#> |  42|Female |         66|         110|           73|    5.88|   1.65|   70.2| 25.75|               0|            0|                   0|                      0|      0|No       |
#> |  35|Female |         60|         125|           68|    5.71|   1.47|   42.5| 19.58|               0|            0|                   0|                      0|      0|No       |
#> |  62|Female |         57|         127|           74|    6.85|   1.52|   47.0| 20.24|               0|            0|                   0|                      0|      0|No       |
#> |  73|Male   |         55|         193|          112|    6.28|   1.63|   57.4| 21.72|               0|            0|                   0|                      0|      0|No       |
#> |  68|Female |         71|         150|           81|    5.71|   1.42|   36.0| 17.79|               0|            0|                   0|                      0|      0|No       |