Synthetic Diabetes Patient Records Dataset

Dataset Features:

• Id: Unique identifier for each data entry.
• Pregnancies: Number of times the patient has been pregnant.
• Glucose: Plasma glucose concentration measured over a 2-hour period during an oral glucose tolerance test.
• Blood_Pressure: Diastolic blood pressure in mm Hg.
• Skin_Thickness: Thickness of the triceps skinfold, measured in mm.
• Insulin: Serum insulin level after 2 hours (mu U/ml).
• BMI: Body mass index, calculated as weight in kg divided by height in m².
• Diabetes_Pedigree: Genetic risk score for diabetes, indicating familial history.
• Age: Age of the patient in years.
• Outcome: A binary variable indicating diabetes status; 1 indicates diabetes presence, while 0 indicates its absence.

Data distribution and Outliers:

Correlations and Relationships:

Usage:

• Diabetes research: To analyze and uncover patterns in diabetes risk factors and demographics.
• Educational purposes: Teaching data science skills such as cleaning, transformation, visualization, and model development within a healthcare context.
• Predictive modelling: Building models that assess diabetes risk, support feature selection, and enable insights into the health indicators of diabetes.

Coverage:

License:

Who can use it:

• Researchers and educators: Ideal for studies and teaching diabetes analytics and healthcare data science.
• Data science enthusiasts and professionals: For practising data manipulation, feature engineering, and machine learning modelling focused on diabetes prediction.