# Lung-Cancer-Prediction-System-Using-Hybrid-CNN-Machine-Learning-Algorithms

Using a CT-Scan image to predict the lung cancer. Machine learning algorithms includes Random Forest, Logistic Regression and Support Vector Machine()

## Models Used

1. Convolutional Neural Network(CNN) - Support Vector Machine(SVM)

2. CNN - Logistic Regression(LR)

3. CNN - Random Forest(RF)

## File Explanation

1. The "**Data_Increasing.ipynb**" file is responsible for generating additional image through data augmentation.

2. The "**Preprocessing_Segmentation.ipynb**" file is involved in both image preprocessing and classification tasks.

3. The "**Lung Cancer Prediction System.ipynb**" file is the main file for the proposed system.

4. The "**dataset**" file stores the lung cancer images, both before and after preprocessing.

5. The "**best_model**" file stores the best model for each type of model used in the system.

6. The "**preprocessing**" file stores the images produced during the preprocessing steps.

7. The "**result**" file stores the images that will be displayed in the Lung Cancer Prediction System.

# References

Dataset used in this project (Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases (IQ-OTH/NCCD) lung cancer datase)

https://www.kaggle.com/datasets/hamdallak/the-iqothnccd-lung-cancer-dataset