Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Integration of artificial intelligence and cloud data engineering is fundamentally changing healthcare decision-making in several domains. From the foundation of strong cloud infrastructure to the forecast modeling of the patient's results, AI-assisted diagnostic imaging, and real-time monitoring systems, these technologies provide unprecedented opportunities to increase clinical practice and adapt resource usage. This change addresses challenges in healthcare distribution for a long time, including information silos, delayed diagnosis, and standardized methods that are responsible for personal variability. While AI-AUGMENTED Healthcare promises more exact diagnosis, personal treatment, and better results, data should address important concerns about data privacy, algorithm transparency, and clinical verification. Successful implementation of these technologies requires attention to the proper position of AI rather than data quality, algorithm verification, workflow integration, and professional decisions and expertise.