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+# 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