I've developed a healthcare diagnosis assistant that enables users to input their symptoms and receive real-time disease predictions. This intuitive system harnesses the power of natural language processing and machine learning to offer quick, reliable healthcare guidance.
https://pontonkid-health-diagno-sys.hf.space
The project is built using the following technologies and frameworks:
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Programming Languages:
- Python 🐍
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Machine Learning Libraries:
- Scikit-learn 🧠
- Gensim 🤖
- TensorFlow (optional)
- PyTorch (optional)
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Data Processing Libraries:
- pandas 🐼
- numpy 🔢
- nltk 📚
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Machine Learning Models:
- Multinomial Naive Bayes (used for symptom-to-disease prediction) 🩺
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Deployment:
- Hugging Face Spaces (for model hosting) 🚀
- Streamlit (for creating the web application) 🌐
- Early Detection: Users receive early warnings about possible medical conditions based on their symptoms
- Symptom Analysis: The system analyzes user-entered symptoms to predict potential diseases.
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Medication Recommendations: I plan to integrate a medication recommendation system, providing users with information on suggested medications and first-aid measures for their predicted diseases.
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Conversational Experience: My future goal is to create a more interactive experience using natural language processing and chatbot capabilities. Users will be able to have in-depth conversations, receive detailed explanations, and get answers to their health-related questions.