Aquaculture is one of the fastest growing food producing sectors worldwide, contributing significantly to food security, nutrition, and the global economy. But disease outbreaks remain a serious problem, threatening sustainability and causing huge financial losses. Recent advancements in artificial intelligence (AI) provide new opportunities for early diagnosis, disease prediction, behavioral monitoring and decision support systems to improve fish health. This review examines the application of AI in fish health management, with an emphasis on machine learning, computer vision, sensor based systems and predictive modeling. The study also highlights current applications, limitations, and future prospects of AI in sustainable aquaculture practices.
Keywords: Fish, Artificial Intelligence, Health Management, Sustainable Aquaculture.