Intelligent online pairing platform for patients with medical consultants

Abstract

In today's rapidly evolving healthcare landscape, technology integration is pivotal in enhancing patient care and resource allocation. This project introduces an intelligent online pairing platform that utilizes the Fuzzy Cluster Means Algorithm (FCM) to match patients with appropriate medical consultants, particularly in pediatric care. The system addresses critical inefficiencies in traditional healthcare management, such as prolonged waiting times, suboptimal resource allocation, and patient dissatisfaction. The platform offers personalized and timely consultations by leveraging artificial intelligence, including Fuzzy logic and clustering techniques. Data collection from Ikot Ekpene General Hospital in Nigeria and secondary data sources provide the foundation for developing the model. The project significantly improves the patient-consultant pairing process, reducing delays and improving healthcare outcomes. Key achievements include the design of a responsive web interface, streamlined appointment scheduling, and robust data privacy measures. The system achieved an accuracy of 85% in matching patients to qualified medical consultants to handle their cases.