Clinical Trials Tracking and Visualization P...

Clinical Trials Tracking and Visualization Pipeline Using NLP

Author Name : R. Gunaditya, Dr. A. Mary Sowjanya

DOI: https://doi.org/10.56025/IJARESM.2024.1209241558

ABSTRACT This paper details the creation of a comprehensive pipeline for tracking, analyzing, and visualizing clinical trials data using Natural Language Processing (NLP) techniques. The developed system integrates state-of-the-art NLP models, including BERT [1] and PEGASUS-PubMed [2], to preprocess and analyze textual data from clinical trials, efficiently handling large datasets of over 350,000 trials. The pipeline supports clustering, document ranking, and summarization, with visualizations generated to enhance data interpretation. The application, built using Flask [3], leverages GPU acceleration to scale with large datasets. The results provide valuable insights into trial outcomes and trends, benefiting both researchers and healthcare professionals