Lung Cancer Risk Factors and Survival is a synthetic lung cancer risk and survival dataset created by Khurram Shahzad and developed under the supervision of Dr. Aammar Tufail, designed as an educational and research resource for lung cancer risk factor analysis, survival research, and machine learning modeling.

The dataset contains 2,000 synthetic patient records covering 60 countries and 6 WHO regions, including demographics, lifestyle and environmental exposures, personal and family medical history, symptoms, tumor characteristics, diagnosis and treatment, and survival outcomes. The data references real-world epidemiological statistics such as WHO and GLOBOCAN 2022, and uses algorithms to generate simulated data with plausible clinical relationships. It contains no real patients or identifiable medical data.

Dataset Composition

The dataset includes the following fields:

• Patient_ID: Patient identifier
• Diagnosis_Year: Year of diagnosis
• Age: Patient age
• Country / WHO_Region: Country and region of residence
• Clinical information: Cancer stage, family history of tumors, smoking exposure, comorbid underlying conditions, treatment plan
• Outcome measures: Survival duration, survival outcome