Published Paper Details:

Medical prescription recognition is a critical task in healthcare for ensuring accurate medication dispensing and improving patient safety. This study presents a novel approach for medical prescription recognition using advanced image processing techniques and machine learning algorithms. Specifically, the method employs Convolutional Neural Networks (CNNs) for feature extraction and classification, leveraging deep learning to analyze and differentiate various handwritten and printed prescriptions based on text, layout, and other distinguishing characteristics. To enhance the robustness of the system, algorithms such as Optical Character Recognition (OCR) for text extraction and Natural Language Processing (NLP) for context understanding are integrated. These techniques address challenges posed by varying handwriting styles, prescription formats, and noise in the images, improving the accuracy and reliability of the recognition system. The proposed method is evaluated against traditional approaches, demonstrating superior performance in terms of precision, robustness, and processing efficiency. This approach not only advances medical prescription recognition technology but also supports improved healthcare management and patient safety, contributing to more effective and efficient healthcare delivery systems.