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Artificial Intelligence-Based Hospital Recommendation System

Author

Listed:
  • Ekwealor, Oluchukwu Uzoamaka

    (Department of Computer Science, Nnamdi Azikiwe University, Awka, Nigeria)

  • Chukwudum, Chiemeka Prince

    (Department of Forensic Science, Nnamdi Azikiwe University, Awka, Nigeria)

  • Betrand, Chidi Ukamaka

    (Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Owerri, Nigeria)

  • Uchefuna Charles Ikenna

    (Department of Computer Science, Federal Polytechnic, Oko, Nigeria)

  • Ibeh, Charles Austeen

    (Department of Forensic Science, Nnamdi Azikiwe University, Awka, Nigeria)

Abstract

This paper is focused on the development of AI-based hospital recommendation system to enable users find suitable healthcare facilities based on location, ratings, and patient reviews. By leveraging machine learning, the system can analyze the patient data and hospital attributes to provide personalized hospital recommendations. During the system development, hospital data, including location, reviews, and ratings were collected, cleaned and prepared for analysis. Machine learning algorithms, such as collaborative filtering and content-based filtering were employed. The best-performing model was selected based on accuracy metrics to ensure personalized recommendation. The system was implemented using PHP, MySQL, HTML, CSS and JavaScript. It is very helpful in the area of patient decision-making as it provides tailored hospital recommendations.

Suggested Citation

  • Ekwealor, Oluchukwu Uzoamaka & Chukwudum, Chiemeka Prince & Betrand, Chidi Ukamaka & Uchefuna Charles Ikenna & Ibeh, Charles Austeen, 2025. "Artificial Intelligence-Based Hospital Recommendation System," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(4), pages 1216-1221, April.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:4:p:1216-1221
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