Dermacare.-.Demo.mp4
- Dermacare is a web-based platform designed to analyze skin conditions based on user uploaded photos. The project provides a user-friendly tool for early detection and diagnosis of skin diseases, enhancing overall skin health awareness.
- We created this project as a social cause because skin diseases continue to be the 4th leading cause of nonfatal disease burden worldwide. However, it is very difficult to provide better dermatological care to under-served or resource-poor regions in a cost-effective manner owing to the unavailability of efficient diagnostic tools, lack of connectivity, and poor laboratory infrastructure etc.
- Thus, developing an Artificial intelligence-based tool (through Image processing technique) for preliminary diagnosis of numerous dermatological conditions will prove to be a boon in the health care system.
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High Accuracy Disease Prediction with Deep Learning: Our website boasts an 80% accurate disease prediction utilizing cutting edge deep learning technology.
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Personalized PDF Report: We provide a comprehensive personalized PDF report for every user, presenting detailed health insights including diagnosis, causes, symptoms, medicines suggestions, and recommendations.
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Email Integration for Report Delivery: Our seamless email integration ensures delivery of the personalized PDF health report to users. This feature enhances user experience, making health information easily accessible.
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Locality Based Hospitals: Our website uniquely offers information about hospitals in the user's locality. This feature ensures swift access to healthcare professionals, adding a practical dimension to our platform.
- Dermacare is built using the MERN (MongoDB, Express.js, React, Node.js) stack.
- Machine Learning Framework: TensorFlow
- Data Visualization: Matplotlib, Seaborn
- Data Handling and Preprocessing: NumPy, Pandas
- Material UI and SCSS are used for designing the website.
Before running Dermacare locally, ensure that you have the following NodeJs and Python installed on your machine.
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Clone the repository:
git clone <repository-url>
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Install dependencies:
For Frontend:
cd frontend npm install
For Backend:
cd backend npm install
For model integration
cd modelBackend pip install -r requirements.txt
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Start the development environment:
For Frontend:
cd frontend npm run start
For Backend:
cd backend npm run start
For model integration
cd modelBackend py app.py
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Access Dermacare:
Open your web browser and navigate to
http://localhost:3000/
to access the Dermacare website.