Abstract

Smart healthcare, propelled by technological advancements, is witnessing a paradigm shift in the way healthcare services are delivered. This paper explores the transformative impact of Computational Intelligence (CI) and Big Data Analytics on smart healthcare systems. Computational Intelligence encompasses artificial neural networks, fuzzy logic, genetic algorithms, and expert systems, while Big Data Analytics involves the processing and analysis of large datasets to extract meaningful insights. This integration aims to enhance the efficiency, accuracy, and personalized nature of healthcare delivery. The application of CI in smart healthcare includes disease diagnosis through medical image analysis and predictive analytics for identifying highrisk patients. Moreover, CI facilitates personalized medicine by tailoring treatment plans based on individual characteristics. On the other hand, Big Data Analytics contributes to clinical decision support, population health management, and real-time monitoring of patients. The combination of CI and Big Data Analytics enables the development of predictive models, decision support systems, and efficient utilization of data from Internet of Things (IoT) devices and sensors. However, the adoption of these technologies in smart healthcare is not without challenges. Privacy and security concerns surrounding patient data, interoperability issues, and ethical considerations demand careful attention. Establishing standards for data interoperability and addressing ethical concerns related to consent and algorithmic biases are imperative for the successful implementation of CI and Big Data Analytics in healthcare.