The rising complexity and operational demands of modern healthcare systems have significantly increased resource usage and associated costs. This trend highlights the need for innovative approaches to optimize workflows and enhance decision-making. From this perspective, the present study explores how artificial intelligence (AI) can contribute to improving efficiency and information access in the medical field. The article begins with an introduction and a concise literature review focused on the integration of AI in healthcare platforms. Also, three main research questions are presented here. Our research employs an evaluation and a comparison for five existing medical-based applications. Each of these platforms was assessed to determine whether and how AI technologies have been integrated into their functionalities. The findings from this analysis inspired us to the design of a novel AI-based architecture, which we propose in section three of the article. This proposed architecture aims to assist medical professionals by providing streamlined access to relevant patient information, using machine learning (ML) techniques. Also, at the end of this section we address the initial research questions. In the final section of the article, we conclude that the insights gained from analyzing existing medical chatbot platforms has informed the design of our AI-based solution, aimed at supporting both patients and healthcare professionals through an integrated and intelligent system. The findings highlight the necessity for systems that not only align with user expectations but also demonstrate seamless integration within clinical workflows. Future research should prioritize advancing the reliability, personalization, and regulatory compliance of these platforms, thereby fostering enhanced patient engagement and enabling healthcare professionals to deliver care that is both more efficient and more accessible.
Zota et al. (Sat,) studied this question.