Abstract
This study focuses on the development of a smart e-prescription and billing system that integrates blockchain, artificial intelligence (AI), and analytics to enhance healthcare services. The system's core features include an AI-driven symptom checker, appointment scheduling, and cryptocurrency-based billing. A systematic review of secondary data from academic studies and industry-related articles was conducted to assess current practices in drug prescription, dispensation, and existing software solutions. The symptom-checker model was trained using a dataset of 4,963 entries, with an 80/20 split between training and testing sets. A Decision Tree Classifier was employed, showing promising performance. The findings suggest that the e-prescription (eRx) application can reduce healthcare costs, minimize prescription errors, and improve the overall quality and efficiency of care. The system was built using frontend web technologies, with Python supporting backend functionalities. Cryptocurrency was implemented as the primary payment method, while machine learning was used to support appointment scheduling. The study recommends reliable internet access and adequate hardware for optimal system performance.
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More From: International Journal of Engineering Research in Computer Science and Engineering
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