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AI-Powered PubMed Query Optimizer (MeSH)

🎯 Research Workflow Automation Tool

For environmental health researchers and spatial epidemiologists, constructing precise search queries for systematic reviews in PubMed can be time-consuming. This tool automates the process by translating natural language research topics into standardized Medical Subject Headings (MeSH) queries using Large Language Models (Llama 3 via Groq API).

📸 Preview: Workflow

This image illustrates how the tool translates a plain English research question into a complex, database-ready MeSH string.

Project Preview

(Note: The output query is immediately ready for use on NCBI PubMed.)

✨ Key Features

  • AI-Driven Translation: Utilizes the llama-3.3-70b-versatile model to understand biomedical context.
  • MeSH Standardization: Ensures output adheres to National Library of Medicine (NLM) tagging standards.
  • Research Efficiency: Reduces the time spent on search strategy design.
  • Clean Interface: Built with Bootstrap 5 for a modern user experience.

🛠️ Technologies

  • Backend: PHP (cURL API handling)
  • AI Inference: Groq Cloud API
  • Frontend: HTML5, Bootstrap 5, JavaScript (AJAX)

🚀 Setup (How to run)

  1. Clone this repository to your local PHP server (e.g., XAMPP).
  2. Get a free API Key from Groq Cloud.
  3. Open config.php and replace 'YOUR_GROQ_API_KEY_HERE' with your actual key.
  4. Open index.php in your browser.

Developed for research automation purposes.