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Lung Cancer Risk is a tabular dataset released in 2025 for lung cancer risk prediction and health factor analysis. It aims to explore the association between smoking habits, lifestyle and lung cancer risk through multidimensional features.

This dataset contains 50,000 patient profiles based on known lung cancer risk factors (such as lifestyle, environmental exposures, and family history). Approximately 25% of positive cases reflect the real-world prevalence of lung cancer. Each sample is comprised of multiple health and behavioral characteristics, making it suitable for lung cancer risk modeling, medical machine learning research, health prediction system development, and educational experiments. It is particularly valuable in classification modeling and risk assessment scenarios.

Data composition:

Each sample contains multiple dimensions of health and behavioral characteristics, including:

• Basic information: age, gender
• Lifestyle habits: smoking status, drinking frequency
• Health factors: chronic diseases (such as hypertension, diabetes), lung-related diagnoses
• Environmental exposures: radon levels, asbestos exposure, secondhand smoke exposure
• Family history: whether there is a history of cancer or lung disease in the family
• Target variable: Lung cancer diagnosis (whether or not)