Artificial Intelligence-Enabled Smart Healthcare Ecosystems for Rural Communities

There is significant potential for AI technology to solve the issues of healthcare disparities between rural and urban areas due to poor medical facilities, scarcity of healthcare workers, and isolated locations. This paper discusses 30 research papers from 2018 to 2026 related to AI technology used in delivering healthcare services in rural areas using different machine learning techniques, deep learning methods, telemedicine, and remote patient monitoring technologies. According to the results, Deep learning methods like CNNs, deliver accurate predictions of 90-97% in diagnosing patients based on medical images, whereas the traditional machine learning techniques predict diseases with an accuracy rate of 80-94% by analyzing structured health records. However, several challenges associated with internet access, cost implications, privacy issues, and digital illiteracy still hinder widespread adoption of AI in rural healthcare services.