An Intelligent System Based on LLMs for Automated Healthcare Data Collection - Guimarães, Nathália C. O. C.; Mello, Felipe C. B.; Fernandes, Talita J.; Campelo, Luís F. H.; Teodoro, João G. M. G.; Soares, Felipe A. L. (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2025)
The Internet contains a large volume of important information for the health sector, spread across several websites. The excess of data and the variety of sources make it difficult to efficiently extract this information. This work proposes to automate this collection using Web Scraping, Natural Language Processing and Language Models. Techniques with BeautifulSoup (for static websites) and Selenium (for dynamic websites) were applied, with support from the GPT-4o-mini model. The tests showed a significant reduction in collection and structuring time. The methodology obtained 90% accuracy on static websites and 73% on dynamic websites. Despite limitations with extensive texts and Document Object Model (DOM) structure, the results show that the approach is viable.