Next-Generation Healthcare Assistance: Study and Development of an Online Recommendation System

Abstract

The demand for personalized and accessible healthcare solutions has led to the development of next-generation assistance systems. This paper focuses on the study and development of an online recommendation system designed to provide tailored healthcare support to individuals. Leveraging advancements in artificial intelligence and data analytics, the system analyzes patient data, medical histories, and other relevant information to generate personalized recommendations for healthcare services, treatments, and lifestyle interventions. Through a combination of machine learning algorithms and user feedback mechanisms, the system continuously learns and adapts to individual preferences and needs, enhancing the quality and effectiveness of recommendations over time. We present a comprehensive overview of the system architecture, data processing techniques, and recommendation algorithms employed in the development process. Additionally, we discuss the potential impact of the system on healthcare delivery, patient outcomes, and overall healthcare accessibility. This work contributes to the advancement of next-generation healthcare assistance solutions, paving the way for more personalized and efficient healthcare delivery in the digital age.

DOI - https://doi.org/10.65525/SVUP.9788199651517.2026.126-129