| Issue |
E3S Web Conf.
Volume 619, 2025
3rd International Conference on Sustainable Green Energy Technologies (ICSGET 2025)
|
|
|---|---|---|
| Article Number | 03016 | |
| Number of page(s) | 9 | |
| Section | Smart Electronics for Sustainable Solutions | |
| DOI | https://doi.org/10.1051/e3sconf/202561903016 | |
| Published online | 12 March 2025 | |
Electronic Health Record classification and analysis using NLP Techniques
1 Department of Artificial Intelligence and Data Science, Vardhaman College of Engineering, Hyderabad, India
2 Department of Artificial Intelligence and Data Science, Vardhaman College of Engineering, Hyderabad, India
3 Department of Artificial Intelligence and Data Science, Lovely Professional University, Phagwara, India
4 Department of Applied Sciences, New Horizon College of Engineering, Bangalore, India
5 Department of Artificial Intelligence and Data Science, Vardhaman College of Engineering, Hyderabad, India
6 Department of Artificial Intelligence and Data Science, Vardhaman College of Engineering, Hyderabad, India
* Corresponding Author: himavamshikanaganti@gmail.com
This paper presents an automated system for the classification and analysis of Electronic Health Records (EHRs) using Natural Language Processing (NLP) techniques. The proposed solution integrates text extraction from PDFs and NLP methods to identify and classify EHR content effectively. By leveraging Python libraries such as PyMuPDF for text extraction and applying NLP preprocessing techniques, the system can handle both structured and unstructured data, providing enhanced accuracy in EHR identification. The approach is validated using a set of EHR and non-EHR documents, achieving promising results in classification accuracy.
Key words: EHR / NLP / PyMuPDF / Stopword / Healthcare
© The Authors, published by EDP Sciences, 2025
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