Automated health check-up interpretation and advice system via web application using rule-based method

Abstract

This study aims to develop an automated health check-up result interpretation and recommendation system via a web application using a Rule-based method. The system is designed to provide accurate interpretations of health check-up results and recommendations. The system was tested using health data from 395 hospital staffs. The results showed that the system performed with the highest accuracy in urine (UA) and fat interpretation, achieving 100% accuracy. The system also performed well in blood sugar interpretation with 99% accuracy, while liver interpretation reached 93%. However, the system failed to detect abnormalities in kidney interpretation, with a sensitivity of 0%, indicating the need for improvement. This study demonstrates the potential of Rule-Based Engines in reducing the workload of healthcare professionals and enhancing convenience in health monitoring, but further refinements are needed to improve detection in certain areas.

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