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Healthcare Diabetes Prediction Dataset
Patient Health Records & Digital Health
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Free
About
This dataset provides medical information and laboratory analysis results for diabetes patients collected from the Iraqi society. It offers essential data for understanding and diagnosing diabetes, a condition often associated with considerable complications. The data was gathered from patient files at the Medical City Hospital and the Specialised Centre for Endocrinology and Diabetes-Al-Kindy Teaching Hospital. It aims to support the development of more accurate methods for diabetes diagnosis.
Columns
- ID: An identifier for each patient record.
- No_Pation: The unique patient number.
- Gender: The patient's gender, categorised as Male or Female.
- AGE: The patient's age in years.
- Urea: Urea levels in the patient's blood.
- Cr: Creatinine ratio in the blood.
- HbA1c: Glycated haemoglobin (HBA1C) levels, indicating average blood sugar.
- Chol: Total cholesterol levels.
- TG: Triglycerides levels.
- HDL: High-density lipoprotein (HDL) cholesterol levels.
- LDL: Low-density lipoprotein (LDL) cholesterol levels.
- VLDL: Very-low-density lipoprotein (VLDL) cholesterol levels.
- BMI: Body Mass Index, a measure of body fat based on height and weight.
- CLASS: The patient's diabetes disease classification, which can be Diabetic, Non-Diabetic, or Predict-Diabetic.
Distribution
The dataset is structured as a CSV file and comprises 14 distinct columns. It contains 1000 valid records, with no missing or mismatched entries for the listed attributes. The file size is approximately 49.51 kB.
Usage
This dataset is well-suited for developing predictive models for diabetes diagnosis and classification, helping to identify patients as Diabetic, Non-Diabetic, or Predict-Diabetic. It can be applied in:
- Building machine learning models for early detection and risk assessment of diabetes.
- Researching the characteristics and patterns of diabetes in the Iraqi population.
- Developing clinical decision support tools for healthcare practitioners.
- Academic studies and educational projects focused on health informatics.
Coverage
The data was specifically collected from the Iraqi society, drawing from medical facilities in Iraq. The demographic scope includes patient ages ranging from 20 to 79 years, with recorded genders comprising approximately 56% male and 43% female individuals. This dataset represents a static collection, as no future updates are anticipated.
License
CC BY-SA 4.0
Who Can Use It
The dataset is beneficial for various users, including:
- Medical researchers aiming to analyse diabetes prevalence, patient profiles, and diagnostic indicators.
- Data scientists and machine learning engineers focused on health-related predictive analytics.
- Public health officials and policy makers interested in regional health trends.
- Students and educators in medical, public health, and data science disciplines for learning and teaching purposes.
Dataset Name Suggestions
- Iraqi Diabetes Patient Analysis
- Diabetes Patient Clinical Data (Iraq)
- Middle Eastern Diabetes Diagnosis Records
- Healthcare Diabetes Prediction Dataset
- Iraqi Blood Sugar & Cholesterol Data
Attributes
Original Data Source: Healthcare Diabetes Prediction Dataset
QUALITY