International Journal of Science, Engineering and TechnologyAuthors: K. Venkat Naveen, Mandati Santosh, Matta Rahul 3, Mr.K.Saravanan
Abstract: AI-driven healthcare diagnostic systems are a critical component of modern medical data analysis, as they directly influence diagnostic accuracy, clinical efficiency, and patient safety. Their primary objective is to assist healthcare professionals by analyzing large volumes of medical data while enabling faster and more reliable clinical decision-making. This paper discusses current technical approaches to AI-assisted healthcare systems, focusing on the application of artificial intelligence, machine learning, and deep learning techniques to process medical images, patient records, and clinical datasets. The relationship between intelligent diagnostic systems and predictive healthcare models is also examined, highlighting their growing importance in next-generation medical technologies. Limitations in traditional diagnostic processes and manual data analysis methods are identified based on observations from recent healthcare practices. These findings emphasize the need for advanced AI-based solutions that enhance diagnostic accuracy, efficiency, and reliability while supporting existing medical workflows rather than replacing healthcare professionals.
