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Early Diabetes Risk Indicators
Patient Health Records & Digital Health
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About
This dataset is designed for early stage diabetes risk prediction, offering a collection of vital sign and symptom data from individuals who either exhibit initial indicators of diabetes or are at risk of developing the condition. It provides valuable insights into potential markers for diabetes onset, encompassing both demographic details and specific symptoms associated with the disease. The dataset serves as a valuable resource for the development and validation of predictive models for early diabetes risk assessment, enabling researchers and healthcare professionals to explore relationships between various symptoms and the likelihood of diabetes development, thereby supporting the advancement of early intervention strategies.
Columns
- Age: The age range of the individuals included in the dataset, from 20 to 65.
- Sex: Gender information of the individuals, classified as Male or Female.
- Polyuria: Indicates the presence of excessive urination (Yes/No).
- Polydipsia: Denotes excessive thirst (Yes/No).
- Sudden Weight Loss: Records instances of abrupt weight loss (Yes/No).
- Weakness: Signifies generalised weakness (Yes/No).
- Polyphagia: Indicates excessive hunger (Yes/No).
- Genital Thrush: Notes the presence of genital thrush (Yes/No).
- Visual Blurring: Describes blurring of vision (Yes/No).
- Itching: Records the presence of itching (Yes/No).
- Irritability: Reflects the display of irritability (Yes/No).
- Delayed Healing: Indicates delayed wound healing (Yes/No).
- Partial Paresis: Denotes partial loss of voluntary movement (Yes/No).
- Muscle Stiffness: Signifies the presence of muscle stiffness (Yes/No).
- Alopecia: Records hair loss (Yes/No).
- Obesity: Indicates the presence of obesity (Yes/No).
- Class: The diabetes classification, categorised as Positive or Negative.
Distribution
The dataset is typically provided as a CSV file, named
diabetes_risk_prediction_dataset.csv. It has a file size of 34.68 kB and contains 17 columns. The dataset comprises 520 records in total, with no missing or mismatched values reported across any of the attributes.Usage
This dataset is ideal for:
- Developing and validating predictive models aimed at early-stage diabetes risk assessment.
- Gaining insights into the correlations between various symptoms and the probability of developing diabetes.
- Advancing early intervention strategies in healthcare by understanding risk factors.
Coverage
The dataset focuses on individuals within an age range of 20 to 65 years. Demographically, it includes both males (63% of records) and females (37% of records). No specific geographic or precise time range coverage details are available in the provided information.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is primarily intended for:
- Researchers involved in medical data analysis, machine learning, and public health studies.
- Healthcare professionals seeking to understand diabetes indicators and improve early diagnosis methods.
Dataset Name Suggestions
- Early Diabetes Risk Indicators
- Diabetic Onset Prediction Data
- Patient Symptom Diabetes Dataset
- Metabolic Risk Factor Data
- Health Symptom Diabetes Classifier
Attributes
Original Data Source: Early Diabetes Risk Indicators
QUALITY