Hybrid Framework for Healthcare System Using SVM

The quick growth of artificial intelligence and machine learning has created fresh prospects in the healthcare sector, particularly in relation to drug recommendation systems. This work explores the design of an intelligent drug recommendation system using artificial intelligence and machine learning in order to provide consistent suggestions based on patient data. By assessing several elements like demographics, medical history, symptoms, and more, the technique suggests a customized strategy to treatment to anticipate the optimum medication. The study underlines the potential of using artificial intelligence and machine learning techniques to ensure fast treatment, reduce human error, and make diagnosis more exact. Notwithstanding the positive outcomes, problems such algorithmic biases, the necessity of large datasets, and data privacy concerns still exist. Crucially, integration of a userfriendly interface and scalability of the system are more important than accuracy. Overall, this paper emphasizes the present limits of artificial intelligence and machine learning as well as the ways in which they may automate drug recommendation, therefore changing healthcare.