Analyze Doctor Receipt with Optical Character Recognition Technology and Machine Learning

Authors: Sumit Patait, Sudarshan Patil, Kalpesh Patil, Roshan Avhad, Prabha Gadakh

Country: India

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Abstract: In this innovative application, we present a Machine Learning-based Doctor Receipt Analyzer system empowered by Optical Character Recognition (OCR) technology. The system represents a transformative leap in the processing of medical receipts by seamlessly integrating advanced OCR algorithms. Capable of extracting critical information from scanned or photographed receipts, the solution automates the traditionally manual task of deciphering handwritten or printed text, enhancing both accuracy and efficiency. Tailored for effortless integration into healthcare administration, the system intelligently decodes essential details such as patient names, dates, services provided, and associated costs. The synergy of machine learning and OCR not only streamlines billing processes for healthcare professionals but also promises to elevate the overall efficiency of medical documentation and financial management, marking a significant advancement in healthcare technology.

Keywords: OCR, Receipt Analyzer, Machine Learning, NLP

Paper Id: 230543

Published On: 2024-04-04

Published In: Volume 12, Issue 2, March-April 2024

Cite This: Analyze Doctor Receipt with Optical Character Recognition Technology and Machine Learning - Sumit Patait, Sudarshan Patil, Kalpesh Patil, Roshan Avhad, Prabha Gadakh - IJIRMPS Volume 12, Issue 2, March-April 2024.

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