Smart Prescription Decoder: An Intelligent Framework for Medicine Receipt Analysis and Alternate Medicine Suggestion using OCR and NLP

Le résumé fourni par la source

The convergence of Artificial Intelligence (AI) and Machine Learning (ML) in health systems is revolutionizing conventional workflows and the delivery of services. In this paper, the design of an AI system that can identify handwritten prescriptions for medicine based on Optical Character Recognition (OCR) and deep learning algorithms is discussed. The prime objective is to read medicine names and related information from free-hand prescriptions automatically and transform unstructured text into structured, machine-readable format. The system draws on a hybrid deep learning framework that combines Convolutional Neural Networks (CNNs) for image feature extraction and Recurrent Neural Networks (RNNs) for sequence text recognition. In addition to data retrieval, the system offers intelligent suggestions for replacement drugs based on a comprehensive pharmaceutical database to facilitate informed decision-making and cost-effective prescription management. The suggested solution significantly reduces manual effort, minimizes errors, and improves overall efficiency in dispensing drugs. This research aims to bring about improved healthcare delivery by offering an accurate, scalable, and intelligent framework for the analysis of prescriptions and suggestion of medicines.

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