Healthcare is evolving rapidly, with AI-powered predictive analytics playing a key role in improving disease diagnosis, personalized treatment, and real-time patient monitoring. Machine learning models are revolutionizing early disease detection, helping identify conditions like diabetes, heart disease, and cancer before they become critical. Deep learning in medical imaging is making diagnosis faster and more accurate, reducing human errors in X-rays, MRIs, and CT scans. Meanwhile, NLP-driven AI assistants are streamlining clinical documentation, saving doctors time and enhancing patient care. Beyond diagnosis, AI is reshaping treatment through personalized medicine, analyzing patient data to recommend the most effective drugs and therapies. Wearable health devices, powered by IoT and AI, are enabling real-time monitoring of vital signs, alerting both doctors and patients to potential health risks. The paper also discusses challenges such as data privacy, ethical concerns, and model bias while showcasing future advancement in AI-driven smart healthcare systems. This paper explores the immense potential of AI in smart healthcare, the hurdles that come with it, and the future of AI-driven patient-centric healthcare systems that can save lives, reduce costs, and improve overall well-being.
Volume 17 | Issue 2
Pages: 8-13