Description

This dataset contains medical and lifestyle information for 1500 patients, designed to predict the presence of cancer based on various features. The dataset is structured to provide a realistic challenge for predictive modeling in the medical domain.

Dataset Structure

Features

1. Age: Integer values representing the patient's age, ranging from 20 to 80.

2. Gender: Binary values representing gender, where 0 indicates Male and 1 indicates Female.

3. BMI: Continuous values representing Body Mass Index, ranging from 15 to 40.

4. Smoking: Binary values indicating smoking status, where 0 means No and 1 means Yes.

5. GeneticRisk: Categorical values representing genetic risk levels for cancer, with 0 indicating Low, 1 indicating Medium, and 2 indicating High.

6. PhysicalActivity: Continuous values representing the number of hours per week spent on physical activities, ranging from 0 to 10.

7. AlcoholIntake: Continuous values representing the number of alcohol units consumed per week, ranging from 0 to 5.

8. CancerHistory: Binary values indicating whether the patient has a personal history of cancer, where 0 means No and 1 means Yes.

9. Diagnosis: Binary values indicating the cancer diagnosis status, where 0 indicates No Cancer and 1 indicates Cancer.

Target Variable

• Diagnosis: The main variable to predict, indicating if a patient has cancer.

Data Distribution

• The dataset is balanced with respect to feature distributions and includes realistic variability in patient data.

Usage

Intended Use

This dataset is intended for training and testing machine learning models for cancer prediction. It can be used for:

• Model training and evaluation.
• Feature importance analysis.
• Algorithm benchmarking.

Disclaimer

This dataset has been preprocessed and cleaned to ensure that users can focus on the most critical aspects of their analysis. The preprocessing steps were designed to eliminate noise and irrelevant information, allowing you to concentrate on developing and fine-tuning your predictive models.

Considerations

• The dataset includes a variety of features known to be associated with cancer risk, making it suitable for exploring different modeling approaches and feature engineering techniques.

Dataset Usage and Attribution Notice

This dataset, shared by Rabie El Kharoua, is original and has never been shared before. It is made available under the CC BY 4.0 license, allowing anyone to use the dataset in any form as long as proper citation is given to the author. A DOI is provided for proper referencing. Please note that duplication of this work within Kaggle is not permitted.

Exclusive Synthetic Dataset

This dataset is synthetic and was generated for educational purposes, making it ideal for data science and machine learning projects. It is an original dataset, owned by Mr. Rabie El Kharoua, and has not been previously shared. You are free to use it under the license outlined on the data card. The dataset is offered without any guarantees. Details about the data provider will be shared soon.