Disease prediction using NLP techniques - Hamza Ouabiba; Farah Sniba (ITM Web of Conferences)
This paper explores the application of the T5 (Text-To-Text Transfer Transformer) model Originating from the groundbreaking “Attention Is All You Need” concept, fine-tuned on a medical dataset to predict diseases and symptoms from unstructured medical reports. By leveraging Natural Language Processing (NLP), the system offers automated analysis, enabling quicker and more accurate diagnoses based on symptoms provided by users. The fine- tuning process involved training the T5 model to adapt to the specific language and context of medical texts. The model’s performance is evaluated based on its ability to detect and predict medical conditions from user inputs.