Medical Report Simplification System: Enhancing Healthcare Accessibility using NLP-based Extraction and AI-Driven Explanation

Medical reports are not easy to understand for patients, due to their complicated medical jargon and terminology. This can cause misunderstandings, making it confusing and prolonging it harder for the people to track their health conditions without guidance from the professionals. To address this issue, an AI (Artificial Intelligence) powered system for the simplification of Medical Report which extracts difficult medical terms and gives explanations that are more user-friendly. The system uses Named Entity Recognition (NER) with SciSpaCy and UMLS (Unified Medical Language System) to identify the medical terms. And then an AI-based explanation generation model powered by Together.Ai's API (Application Programming Interface) is used to ensure clarity and readability. This initiative, aims to close the communication gap between healthcare providers and patients by turning difficult medical reports into clear explanation, ultimately enabling users to make well-informed health choices.