MedPDF : An Intelligent AI model for interactive PDF Analysis of Health Care Documents

Authors

  • Antony Vigil M S
  • Adithya S
  • Abinesh Vardan S L
  • Vamsi T

Keywords:

Natural Language Processing (NLP), Machine Learning, Optical Character Recognition (OCR), Text Extraction, Summarization, Information Retrieval

Abstract

PDFs are the new standard for delivering a variety of information in the digital environment that we live in today. However, it can be a great deal of time and effort to do a deep analysis and interaction. A brand new artificial intelligence (AI) system called "MedPDF" is aimed at paving the way for smooth and natural-style conversations with medical documents and reports. Through the use of machine learning and natural language processing (NLP), users get the possibility to inquire about and get predefined responses that are generated and converted from the source of the document rather than being manually written. For some of the user issues, "MedPDF" would be an easy answer: document processing for medical report retrieval. "MedPDF" aspires to change the way into which people handle undigested data in PDF format by integrating the latest and most powerful techniques of AI and NLP. MedPDF employs deep learning models to excel in correctly inferring a passage, for which it produces high accuracy scores with an average precision of 92.5%, recall of 89.7%, and F1-score of 91.1%.

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Published

2025-05-29

How to Cite

1.
M S AV, S A, S L AV, T V. MedPDF : An Intelligent AI model for interactive PDF Analysis of Health Care Documents. J Neonatal Surg [Internet]. 2025May29 [cited 2025Sep.20];14(29S):61-8. Available from: https://www.jneonatalsurg.com/index.php/jns/article/view/6712

Issue

Vol. 14 No. 29S (2025): Journal of Neonatal Surgery

Section

Original Article

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