A Review of Al-Based Conversational Systems in Healthcare Informatics

Artificial intelligence (AI) has significantly transformed healthcare services by enabling intelligent automation, decision support, and enhanced patient-provider interaction. Among these advancements, AI-based conversational systems such as medical chatbots and virtual health assistants have gained increasing attention. These systems leverage natural language processing (NLP), machine learning (ML), deep learning (DL), and large language models (LLMs) to provide services including patient inquiry handling, appointment scheduling, symptom assessment, chronic disease monitoring, and health education. This paper presents a systematic review of AI-based conversational systems in healthcare informatics, focusing on peer-reviewed studies published between ۲۰۱۸ and ۲۰۲۵. The reviewed literature is categorized based on underlying technologies and application domains. The results indicate that conversational AI systems improve patient engagement, accessibility, and operational efficiency. However, challenges related to clinical reliability, data privacy, and ethical compliance remain significant. Future research directions emphasize the integration of large language models with intelligent agents and secure healthcare infrastructures.

کلیدواژه ها:

Artificial Intelligence ، Conversational Systems ، Medical Chatbots ، Healthcare Informatics ، Natural Language Processing