An intelligent expert system that diagnoses common diseases based on user-described symptoms using rule-based reasoning (via Experta) and Natural Language Processing (via spaCy and NLTK). The system also provides health precautions for each diagnosed disease.

This system simulates a basic medical diagnostic process. Users can describe their symptoms in natural language, and the system will:

1. Understand the input using NLP (tokenization, lemmatization, stemming).
2. Match the extracted symptoms with predefined rules (using Experta).
3. Diagnose the most likely disease.
4. Recommend suitable precautions for the diagnosed disease.

The system uses the Experta rule-based engine (based on CLIPS) to model relationships between diseases and their symptoms. Each disease is defined as a rule that is triggered when a sufficient number of its associated symptoms are identified in the user's input.

NLP preprocessing is performed using:

• spaCy for:

  • Tokenization
  • Lemmatization

• NLTK for:

  • Stemming
  • Stopword removal
  • Symptom keyword matching

This combination ensures robust handling of user-provided natural language inputs.

The system uses a CSV file with the following structure:

I have itching and skin rash.

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Diagnosis: Based on the symptoms you've provided, it seems you might have Fungal Infection.

Precautions:

Bath twice daily.

Use Dettol or neem in your bathing water.

Keep the infected area dry.

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git clone https://github.com/yourusername/medical-diagnosis-expert-system.git
cd medical-diagnosis-expert-system
2. Install Dependencies
bash
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pip install -r requirements.txt
Example requirements.txt:

nginx
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experta
nltk
spacy
pandas
Make sure to download necessary NLTK and spaCy resources:

python
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import nltk
nltk.download('punkt')
nltk.download('stopwords')

# For spaCy
import spacy
spacy.cli.download("en_core_web_sm")
3. Run the System
bash
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python main.py
📦 Tech Stack
🧠 Experta – rule-based expert system

🧬 spaCy – NLP preprocessing

🧪 NLTK – text analysis (stemming, stopwords)

📊 Pandas – data handling