Personalized Healthcare: A Comprehensive Approach for Symptom Diagnosis and Hospital Recommendations Using AI and Location Services

Authors

• Seng-Keong Tan, Multimedia University, Malaysia
• Siew-Chin Chong, Multimedia University, Malaysia
• Kuok-Kwee Wee, Multimedia University, Malaysia
• Lee-Ying Chong, Multimedia University, Malaysia

Corresponding Author ORCID Identifer

Siew-Chin Chong https://orcid.org/0000-0003-0421-4367

Section

Regular Issue

Abstract

Utilizing digital advancements, an integrated Flask-based platform has been engineered to centralize personal health records and facilitate informed healthcare decisions. The platform utilizes a Random Forest model-based symptom checker and an OpenAI API-powered chatbot for preliminary disease diagnosis and integrates Google Maps API to recommend proximal hospitals based on user location. Additionally, it contains a comprehensive user profile encompassing general information, medical history, and allergies. The system includes a medicine reminder feature for medication adherence. This innovative amalgamation of technology and healthcare fosters a user-centric approach to personal health management.

Cite This Article

Tan, S.-K., Chong, S.-C., Wee, K.-K., & Chong, L.-Y. (2024). Personalized Healthcare: A Comprehensive Approach for Symptom Diagnosis and Hospital Recommendations Using AI and Location Services. Journal of Informatics and Web Engineering, 3(1), 117–135. https://doi.org/10.33093/jiwe.2024.3.1.8

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.