Navigating the Healthcare Landscape with Recommendation Systems: A Survey of Current Applications and Potential Impact

Recommendation systems in healthcare are designed to provide personalized medical treatment and advice to patients by analyzing large amounts of data. These systems use various algorithms, they are content-based filtering, collaborative filtering, and hybrid methods, to analyze patient data and make recommendations. The integration of these systems is done with electronic health records (EHRs) that improves the accuracy of the recommendations. The applications of recommendation systems in healthcare include personalized medicine, disease management, and telemedicine. However, the use of these systems also raises concerns about privacy and bias. This paper surveys the present state-of-the-art in recommendation systems in healthcare, and discusses the potential applications, challenges and future directions in this field.