Next-Gen EHR: Advancing Healthcare with Integrated Recommendations and Decision Support
DOI:
https://doi.org/10.64252/ps1ts012Keywords:
EHR, Health recommendation, Prediction, Naive Bayes, SVMAbstract
The study outlines a holistic strategy for modernizing healthcare administration through the fusion of electronic health records (EHR) and machine learning techniques, including Support Vector Machines (SVM) and Naive Bayes. It addresses challenges in manual patient record management, particularly in countries like India, by proposing an EHR system implementation. The developed web application combines frontend and backend development technologies to streamline record management, enhance data accuracy, and improve healthcare delivery. Additionally, leveraging Naive Bayes and SVM algorithms, the system prioritizes multimedia efficiency and offers health recommendation by analyzing unstructured EHRs. This research contributes to advancing predictive healthcare analytics by exploring the integration of EHRs and machine learning for health recommendation, aiming to enhance patient outcomes and healthcare quality. The findings of this underscore the strength of machine learning in revolutionizing health recommendation and personalized healthcare, thereby paving the way for improved patient care and management.