Citation
Tan, Seng-Keong and Chong, Siew-Chin and Wee, Kuok-Kwee and Chong, Lee-Ying (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). pp. 117-135. ISSN 2821-370X
Text
795-Article Text-5711-1-10-20231221.pdf - Published Version Restricted to Repository staff only Download (1MB) |
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.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Random Forest Model, OpenAI API, Personal Health Records, Symptom Diagnosis, Google Maps API |
Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA71-90 Instruments and machines Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software |
Divisions: | Others |
Depositing User: | Mr. MUHAMMAD AZRUL MOSRI |
Date Deposited: | 02 Apr 2024 06:51 |
Last Modified: | 02 Apr 2024 06:51 |
URII: | http://shdl.mmu.edu.my/id/eprint/12246 |
Downloads
Downloads per month over past year
Edit (login required) |