Hybrid AI Models to Enhance Quality of Service in Healthcare Wireless Networks

Healthcare companies are depending more on wireless networks to send data and do remote monitoring. Healthcare systems find it challenging to efficiently provide premium services under conditions like congestion, data loss, and latency. This effort aims to investigate if hybrid artificial intelligence models may improve the quality of service of wireless networks by means of healthcare facilities. More effective data transmission, improved real-time monitoring, and safer patient care might all follow from this. This work uses machine learning techniques like ANN, SVM, and RL in order to enhance data routing, lower network congestion, and guarantee consistent data transfer. By guaranteeing the timely transmission of essential health data and adjusting to changing network conditions, the proposed hybrid architecture significantly improves service quality generally.