Synthetic Asthma Disease Patient Records Dataset

Dataset Features

• tiredness: Whether the individual experiences tiredness.
• dry_cough: Whether the individual experiences dry cough.
• difficulty_in_breathing: Whether the individual experiences difficulty in breathing.
• sore_throat: Whether the individual experiences sore throat.
• none_symptom: Whether the individual has no symptoms.
• pains: Whether the individual experiences body pains.
• nasal_congestion: Whether the individual has nasal congestion.
• runny_nose: Whether the individual experiences a runny nose.
• none_experiencing: Whether the individual is not experiencing any symptoms.
• severity: The severity of asthma symptoms (e.g., "mild", "low", "moderate", "high").
• age: The age of the individual.
• gender: The gender of the individual.

Distribution

Usage

• Asthma Severity Prediction: Build machine learning models to predict the severity of asthma based on the symptoms and demographic factors.
• Symptom Analysis: Analyze the relationship between asthma symptoms (e.g., dry cough, difficulty in breathing) and asthma severity.
• Demographic Impact Study: Investigate how age and gender influence the occurrence and severity of asthma symptoms.
• Personalized Care: Use the dataset to develop models for personalized asthma care plans based on symptom patterns and severity.
• Healthcare Research: Study patterns in asthma symptom occurrence and severity across different age groups and genders.

License

Who Can Use It

• Data Science Practitioners: For practicing data preprocessing, classification, and regression tasks.
• Healthcare Researchers: To explore the relationships between asthma symptoms, severity, and demographic factors.
• Medical Professionals: To better understand asthma patterns and assist in treatment decision-making.
• Public Health Analysts: To analyze asthma prevalence and symptom severity across different populations.
• Policy Makers: To develop better healthcare policies related to asthma management and prevention.