> ## Documentation Index
> Fetch the complete documentation index at: https://docs.medtechai.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Integration Guide

> Get started with our medical datasets in minutes.

# Integration Guide

Get started with our medical datasets in minutes.

<Steps>
  <Step title="Download Dataset">
    Access your purchased datasets through our secure download portal. You can find sample datasets [here](/datasets/samples).
  </Step>

  <Step title="Load JSON Data">
    Import the structured JSON files into your preferred development environment.
  </Step>

  <Step title="Train Your Model">
    Use the instruction-input-output format for fine-tuning or training your AI models.
  </Step>
</Steps>

## Code Examples

<Tabs>
  <Tab title="Python (Pandas)">
    ```python theme={null}
    import json
    import pandas as pd

    # Load medical dataset
    with open('medicationqa.json', 'r') as f:
        data = json.load(f)

    # Convert to DataFrame
    df = pd.DataFrame(data)

    # Prepare training data
    training_data = df[['instruction', 'input', 'output']]

    # Example: Filter medication-related questions
    medication_qs = df[df['input'].str.contains('medication|drug|pill')]

    print(f"Total entries: {len(df)}")
    print(f"Medication questions: {len(medication_qs)}")
    ```
  </Tab>

  <Tab title="JavaScript (Node.js)">
    ```javascript theme={null}
    const fs = require('fs');

    // Load medical dataset
    const data = JSON.parse(fs.readFileSync('medicationqa.json', 'utf8'));

    // Process data for chatbot training
    const trainingPairs = data.map(item => ({
        question: item.input,
        answer: item.output,
        context: item.instruction
    }));

    // Example: Search functionality
    function searchMedicalAnswer(query) {
        return data.filter(item => 
            item.input.toLowerCase().includes(query.toLowerCase())
        );
    }
    ```
  </Tab>
</Tabs>

## API Integration Example

<Tabs>
  <Tab title="REST API (Express.js)">
    ```javascript theme={null}
    // Express.js API endpoint
    app.get('/api/medical-qa', (req, res) => {
        const { query, category } = req.query;
        
        let results = medicalData;
        
        if (query) {
            results = results.filter(item => 
                item.input.toLowerCase().includes(query.toLowerCase())
            );
        }
        
        if (category) {
            results = results.filter(item => 
                item.instruction.includes(category)
            );
        }
        
        res.json({
            results: results.slice(0, 10),
            total: results.length
        });
    });
    ```
  </Tab>

  <Tab title="Frontend (React)">
    ```javascript theme={null}
    // React component example
    const MedicalChatbot = () => {
        const [query, setQuery] = useState('');
        const [response, setResponse] = useState('');
        
        const askQuestion = async () => {
            const result = await fetch(
                `/api/medical-qa?query=${encodeURIComponent(query)}`
            );
            const data = await result.json();
            
            if (data.results.length > 0) {
                setResponse(data.results[0].output);
            } else {
                setResponse('No results found.');
            }
        };
        
        return (
            <div>
                <input value={query} onChange={e => setQuery(e.target.value)} />
                <button onClick={askQuestion}>Ask</button>
                <div>{response}</div>
            </div>
        );
    };
    ```
  </Tab>
</Tabs>