This Android application is designed to assist users in identifying potential signs of skin cancer using image analysis and classification techniques. By leveraging machine learning algorithms, this app aims to provide preliminary evaluations of skin lesions to raise awareness and prompt users to seek professional medical advice when necessary.
- Image Upload: Users can upload images of skin lesions or moles directly from their device's gallery or capture a new image using the app's camera feature.
- Image Processing: Utilizes machine learning models to process and analyze the uploaded images to detect potential signs of skin cancer.
- Classification Results: Provides users with an initial classification of the skin lesion, indicating whether it falls into benign or potentially malignant categories.
- Educational Resources: Offers information and educational content about various types of skin lesions, signs of skin cancer, and preventive measures.
- Clone or download the repository from [GitHub link].
- Open the project using Android Studio.
- Connect your Android device to your computer.
- Build and run the application on your device through Android Studio.
- Launch the application on your Android device.
- Select the option to upload an image from the gallery or use the camera to capture a new image of the skin lesion.
- Follow the on-screen instructions to confirm and submit the image for analysis.
- Wait for the app to process the image and provide the classification results.
- Review the classification and any additional information provided by the app.
- For accurate medical assessment, consult a healthcare professional if the classification indicates a potential risk.
- Android Studio: Development environment for building the Android application.
- Machine Learning: Utilizes machine learning algorithms and models for image analysis and classification.
- Java/Kotlin: Programming languages used for the app development.
- TFLite: Model inference runtime.