Semantic Understanding And Contextual Explanation of Medical Documents

Authors

  • Ch Mahender Reddy Assistant Professor, Department of CSE, GITAM University, Hyderabad, India Author
  • K Sai Varun Reddy Undergraduate, Department of CSE, GITAM University, Hyderabad, India Author
  • M Uday Sreechand Undergraduate, Department of CSE, GITAM University, Hyderabad, India Author
  • TN Sai Ram Undergraduate, Department of CSE, GITAM University, Hyderabad, India Author
  • T Ajith Karthikeya Undergraduate, Department of CSE, GITAM University, Hyderabad, India Author

DOI:

https://doi.org/10.33425/3066-1226.1080

Keywords:

Medical Document Processing, Optical Character Recognition (ocr), Natural Language Processing (NLP), Paddle OCR, GPT API, Health Informatics Patient Centered Healthcare, Diagnostic Report Summarization

Abstract

This study introduces an AI-driven system designed to efficiently extract and summarize medical documents using Optical Character Recognition (OCR) and Natural Language Processing (NLP). By leveraging Tesseract OCR, the system accurately retrieves textual data from diagnostic reports. The extracted content is then processed through a GPT-based API to generate brief, patient friendly summaries in 2-3 lines. By simplifying complex medical terms, the system enhances patient understanding, supports informed decision-making, and improves communication between healthcare professionals and patients. This method seeks to bridge the gap between technical medical reports and patient awareness, ultimately contributing to better healthcare outcomes. The implementation is conducted on Google Colab, ensuring cloud-based execution for improved scalability and accessibility.

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Published

2025-07-24

Issue

Vol. 5 No. 1

Section

Articles