Conversational Agents in Healthcare: Design and Implementation

The integration of conversational agents in healthcare has emerged as a transformative tool for delivering personalized, scalable, and accessible care. These intelligent systems, powered by AI and NLP, hold the potential to revolutionize patient interactions, enhance clinical decision-making, and provide continuous support for individuals across various healthcare settings. This chapter explores the design and implementation of healthcare conversational agents, with a focus on personalization, adaptability, and ethical considerations. Key challenges related to user modeling, real-time feedback incorporation, and maintaining clinical safety while providing flexible, patient specific responses are discussed. Special emphasis was placed on the unique needs of pediatric, elderly, and disabled populations, highlighting how adaptive conversational agents can cater to their diverse requirements. The chapter examines emotion-aware and empathy-driven strategies that enhance user engagement and satisfaction, as well as the critical role of patient feedback in shaping adaptive responses. The intersection of technology, healthcare, and user-centric design principles was explored, offering insights into the future potential and ethical implications of conversational agents in healthcare.