MedicaLLM Evaluation

Comprehensive evaluation platform for medical AI systems and algorithms

Medical LLM Evaluation

About LLM Evaluation

Our project, Medical LLM Evaluation, addresses a critical need in healthcare: ensuring AI-powered language models provide accurate, safe, and culturally relevant information. We've developed a comprehensive framework to evaluate the performance of Large Language Models (LLMs) in answering questions related to maternal health in multiple languages, including English, Hindi, and Marathi. Our work is essential for validating AI tools before they are used by patients and healthcare providers.

Our Solution

🔬

Comprehensive AI model testing and validation protocols.

📚

A gold-standard dataset of questions and answers created and validated by local medical experts.

⚖️

A professionally weighted scoring system to determine the clinical accuracy, completeness, and contextual safety.

📊

Evaluation of responses on multiple dimensions: medical quality, semantic similarity, and language quality.

🗣️

Focus on low-resource languages like Hindi and Marathi to ensure linguistic accessibility and cultural relevance.

🧠

Utilization of state-of-the-art NLP models like Cohere's Command-A and Aya Expanse for multilingual QA.

A holistic final score that aggregates medical, semantic, and linguistic quality for a complete performance metric.

Medical Evaluation Scores

Why LLM Evaluation Stands Out

Unique Value

  • Comprehensive multi-dimensional evaluation framework
  • Real-time bias detection and mitigation tools
  • Regulatory compliance and safety assessment
  • Clinical validation with healthcare partners

Evidence of Success

6+
AI Models Evaluated
*Including Cohere's Command-A and Aya
3
Languages Supported
English, Hindi, Marathi
Automated + LLM-as-a-Judge
Dual Scoring System

*Semantic Similarity, Linguistic Analysis, and LLM-based Evaluation.

Medical LLM Evaluation Platform Showcase

These slides demonstrate our comprehensive approach to assessing medical AI systems, featuring our dashboard interface, scoring mechanisms, and validation methodologies.

Medical LLM Evaluation Dashboard
AI Model Performance Analysis
Clinical Decision Support
Healthcare Data Visualization
Medical AI Research Platform
Clinical Outcome Metrics
AI Model Validation Results
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Meet the Team

Varun Nair

Varun Nair

Machine Learning Engineer

D.J. Sanghvi College of Engg.

B. Tech Computer Engineering ‘ 25

Himanshu Beniwal

Himanshu Beniwal

Mentor

PHD Student

Indian Institute of Technology Gandhinagar

Dhara Mungra

Dhara Mungra

CTO

Data Scientist

MS, New York University

Swapneel Mehta

Swapneel Mehta

Chief Scientist

Postdoc, MIT & Boston University

Ph.D. New York University