Improved ease of use for the researchers and make the platform more intuitive.

Achieved 98.2 % accuracy on the test data.

OBJECTIVE

Process the natural language queries (text and voice) on the clinical trials analytics platform posed by researchers.

PROJECT HIGHLIGHTS AND CHALLENGES

• Processed complex textual queries using entity recognition and text classification techniques.
• Feedback loop to retrain the model.
• Achieved 98.2 % accuracy on the test data.
• Integration with Google’s speech-to-text engine.