A Comprehensive Review of AI Applications in Smart Healthcare Systems

This study explores current developments in the use of artificial intelligence (AI) for healthcare applications, with particular emphasis on predicting cardiovascular conditions, identifying blood groups, scheduling clinical appointments, and optimizing emergency ambulance services. Techniques involving deep learning—such as Convolutional Neural Networks (CNN), EfficientNet, InceptionV3, and MobileNetV2—are commonly used for processing images like retinal and fingerprint scans. The reviewed literature showcases how these approaches support early diagnosis, enable contactless blood group determination, and assist in continuous patient tracking. The literature highlights emerging challenges including model explainability, dataset limitations, integration with hospital infrastructure, and the need for scalable, secure, and patient-centered solutions.