Mobile-Based Electronic Health Record System

Phua, Hong Yip (2026) Mobile-Based Electronic Health Record System. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

In today’s healthcare environment, the need for fast, safe and centralized access to patient information is increasing. However, many healthcare institutions still use traditional systems which are unable to effectively manage appointments, medical history and other. This propose of this project is to address that gap by introducing a mobile-based Electronic Health Record (EHR) system that allow patient and healthcare professionals to access and manage information effectively. The system comprises user authentication, appointment booking, secure data storage, a chat module, and medical report generation. Furthermore, the project uses artificial intelligence (AI) tools to improve decision-making. The system focus on three AI tools which are a No-Show prediction module that helping clinics predict whether patients will miss appointments, a glaucoma detection model that analyzing retinal funds images to detect signs of glaucoma, and a symptom-based infectious disease prediction can diagnose whether there is disease based on symptoms. These tools are integrated into mobile application to provide assistance to patients and doctors. The methodology used includes XGBoost, LightGBM, and CatBoost for appointment predictions; ResNet50, DenseNet121, and EfficientNetB0 for glaucoma image classification; and Logistic Regression, SVM, and Naive Bayes for symptom-based disease prediction. The system is designed by mobile development tools like Flutter and trained using real-world datasets from Kaggle. The testing included verifying each module’s performance and user acceptance. The project successful showing the power of integrating mobile and AI to improve healthcare operations. Finally, the system could help create smarter digital healthcare services in local clinics and through telemedicine.