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Predictive Factors for Lung Cancer
Patient Health Records & Digital Health
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About
Exploring various attributes and lifestyle factors to predict the likelihood of lung cancer, this data aims to support cancer prediction systems. It enables individuals to understand their cancer risk affordably and make informed decisions about their health. The data was gathered from an online lung cancer prediction system and contains multiple attributes related to patient symptoms and habits.
Columns
- GENDER: The gender of the patient, recorded as 'M' for male and 'F' for female.
- AGE: The age of the patient in years.
- SMOKING: Indicates if the patient smokes, where 2 represents 'YES' and 1 represents 'NO'.
- YELLOW_FINGERS: Indicates the presence of yellow fingers, where 2 represents 'YES' and 1 represents 'NO'.
- ANXIETY: Indicates if the patient experiences anxiety, where 2 represents 'YES' and 1 represents 'NO'.
- PEER_PRESSURE: Indicates if the patient experiences peer pressure, where 2 represents 'YES' and 1 represents 'NO'.
- CHRONIC DISEASE: Indicates if the patient has a chronic disease, where 2 represents 'YES' and 1 represents 'NO'.
- FATIGUE: Indicates if the patient experiences fatigue, where 2 represents 'YES' and 1 represents 'NO'.
- ALLERGY: Indicates if the patient has allergies, where 2 represents 'YES' and 1 represents 'NO'.
- WHEEZING: Indicates if the patient experiences wheezing, where 2 represents 'YES' and 1 represents 'NO'.
- ALCOHOL CONSUMING: Indicates the patient's alcohol consumption status, where 2 represents 'YES' and 1 represents 'NO'.
- COUGHING: Indicates if the patient has a cough, where 2 represents 'YES' and 1 represents 'NO'.
- SHORTNESS OF BREATH: Indicates if the patient experiences shortness of breath, where 2 represents 'YES' and 1 represents 'NO'.
- SWALLOWING DIFFICULTY: Indicates if the patient has difficulty swallowing, where 2 represents 'YES' and 1 represents 'NO'.
- CHEST PAIN: Indicates if the patient experiences chest pain, where 2 represents 'YES' and 1 represents 'NO'.
- LUNG_CANCER: The target variable indicating the lung cancer diagnosis, recorded as 'YES' or 'NO'.
Distribution
The dataset is provided in a CSV file format named
lung cancer survey.csv, with a size of approximately 11.28 kB. It contains 309 instances (rows) and 16 attributes (columns).Usage
This dataset is ideal for developing and training machine learning models for cancer risk prediction. It can be used for academic research into the correlational factors of lung cancer, public health studies, and creating low-cost diagnostic aid tools.
Coverage
The dataset's geographic and demographic scope is not explicitly defined. It contains data for 309 individuals, with ages ranging from 21 to 87. The gender distribution is approximately 52% male and 48% female.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: To build predictive models for early cancer detection.
- Healthcare Researchers and Academics: To study the relationships between various risk factors and lung cancer.
- Public Health Officials: To analyse population-level risk factors and inform public health campaigns.
- Students: As a practical dataset for projects in data analysis, statistics, and machine learning.
Dataset Name Suggestions
- Lung Cancer Risk Factor Survey
- Predictive Factors for Lung Cancer
- Lung Cancer Symptom and Lifestyle Data
- Patient Data for Lung Cancer Prediction
- Survey of Lung Cancer Correlates
Attributes
Original Data Source: Predictive Factors for Lung Cancer
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