Abstract
<jats:p>This research investigates the role of edge computing in enhancing artificial intelligence (AI) applicationswithin the healthcare sector. By comparing edge computing to traditional cloud computing, the studyfocuses on key performance metrics such as latency, bandwidth consumption, data privacy, real-timeprocessing efficiency, storage costs, and response time for critical alerts. The results demonstrate thatedge computing significantly reduces latency and bandwidth usage while improving data security andreal-time processing capabilities, making it a superior choice for AI-powered healthcare applicationssuch as diagnostics, predictive analytics, personalized medicine, and remote patient monitoring. Thefindings highlight the potential of edge computing to address the growing demands of AI in healthcareby providing more efficient, secure, and responsive solutions, ultimately improving patient outcomes andoperational efficiency in healthcare environments.</jats:p>