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This project focuses on the detection of lung cancer using an Artificial Neural Network (ANN) model in Python with an accuracy rate of 96%. By leveraging patient data, the ANN model is trained to classify and predict the presence of lung cancer accurately. Implemented in Google Colab, the model goes through data preprocessing, training, and testing

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mucahitmoonstar/Lung-Cancer-Detection

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"Detecting Lung Cancer with 96% Accuracy Using an Artificial Neural Network (ANN) Model in Google Colab"

This project utilizes an Artificial Neural Network (ANN) algorithm to detect lung cancer with a high accuracy rate of 96% in Python. Implemented in Google Colab, the project aims to classify and predict lung cancer presence based on various medical data inputs. The ANN model is trained and tested on a labeled dataset containing relevant health and diagnostic information. Through data preprocessing, training, and evaluation, the model achieves a high level of accuracy, demonstrating its potential as a support tool for early detection of lung cancer, which is critical for effective treatment and patient outcomes.

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This project focuses on the detection of lung cancer using an Artificial Neural Network (ANN) model in Python with an accuracy rate of 96%. By leveraging patient data, the ANN model is trained to classify and predict the presence of lung cancer accurately. Implemented in Google Colab, the model goes through data preprocessing, training, and testing

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