🎗️ Lung Cancer Predictor

📋 Table of Contents

1. Introduction
2. Features
3. Technologies Used
4. How It Works
5. API Endpoint
6. Flutter App
7. Installation
8. Usage
9. Video Demo
10. Author

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🌟 Introduction

The Lung Cancer Predictor is a machine learning-based application designed to predict the likelihood of lung cancer based on various health-related features. This project consists of:

• A FastAPI backend that serves a machine learning model for predictions.
• A Flutter frontend that allows users to input their health data and view predictions.

📌 Source: The dataset is derived from Kaggle. Dataset link: [Lung Cancer Predict Dataset].

This project aims to provide an easy-to-use tool for individuals to assess their risk of lung cancer based on key health indicators.

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🚀 Features

• FastAPI Backend:
  • RESTful API endpoint for making predictions.
  • Input validation using Pydantic.
  • Hosted on Render for public access.
• Flutter Frontend:
  • User-friendly interface for inputting health data.
  • Displays prediction results or error messages.
  • Supports multiple pages for input and results.
• Machine Learning Model:
  • Trained on a dataset with multiple health-related features.
  • Predicts the likelihood of lung cancer (binary classification).

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🛠️ Technologies Used

• Backend:
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• Frontend:
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• Hosting:
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🧠 How It Works

1. Data Collection:
   • The model is trained on a dataset containing features such as age, gender, smoking status, oxygen saturation, and more.
2. Model Training:
   • A linear regression model is trained to predict the likelihood of lung cancer.
3. API Deployment:
   • The trained model is serialized and integrated into a FastAPI backend.
4. User Interaction:
   • Users input their health data into the Flutter app.
   • The app sends the data to the FastAPI endpoint.
   • The API returns the prediction, which is displayed in the app.

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🔗 API Endpoint

The FastAPI backend provides a single endpoint for making predictions:

• URL: (https://linear-regression-model-ntlf.onrender.com)
• Method: POST
• Input: JSON object with the following fields:

  {
    "AGE": 45,
    "GENDER": 1,
    "SMOKING": 0,
    "FINGER_DISCOLORATION": 0,
    "MENTAL_STRESS": 1,
    "EXPOSURE_TO_POLLUTION": 0,
    "LONG_TERM_ILLNESS": 0,
    "ENERGY_LEVEL": 7.5,
    "IMMUNE_WEAKNESS": 0,
    "BREATHING_ISSUE": 0,
    "ALCOHOL_CONSUMPTION": 1,
    "THROAT_DISCOMFORT": 0,
    "OXYGEN_SATURATION": 98.0,
    "CHEST_TIGHTNESS": 0,
    "FAMILY_HISTORY": 0,
    "SMOKING_FAMILY_HISTORY": 0,
    "STRESS_IMMUNE": 0
  }

• Output: JSON object with the prediction:

  {
    "prediction": No Lung Cancer(0)
  }

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📱 Flutter App

The Flutter app provides a user-friendly interface for interacting with the API. It includes:

• Input Page:
  • TextFields for each input variable.
  • A "Predict" button to submit the data.
• Result Page:
  • Displays the prediction result or an error message.

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🛠️ Installation

1. Clone the repository:

   git clone https://github.com/Irenee123/linear_regression_model.git
   cd Summative/lung-cancer

2. Install dependencies:

   flutter pub get

3. Run the app:

   flutter run

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🎮 Usage

1. Open the Flutter app.
2. Enter your health data in the input fields.
3. Click the "Predict" button.
4. View the prediction result on the next page.

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📹 Video Demo

Watch the video demo of the Lung Cancer Predictor in action:
*(Video DEMO and Model explaination.)*

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👤 Author

• Irenee Gisubizo Dusingizimana
  • GitHub: Irenee123
  • Email: [i.dusingizi@alustudent.com]

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