Conversational Health Bots for Telemedicine Services: Survey
DOI:
https://doi.org/10.25195/ijci.v50i2.508Keywords:
natural language processing (NLP), chatbot, argumentation, machine learning (ML), recommendations.Abstract
An increasing number of individuals take refuge in telemedicine systems for medical diagnosis and treatment due to their numerous benefits, including reduced healthcare costs, enhanced efficiency, and the ability to treat and prevent a wide range of physical and mental health problems. To improve the health status and clinical findings of older and underserved individuals, healthcare institutions have expanded telemedicine services, integrating them with advanced assisted living systems and environments. Conversational chatbots, or dialogue systems, are software tools designed to emulate human interaction via the Internet. These conversational bots can engage in natural conversations and can be merged into websites, mobile apps, and messaging platforms.
Moreover, they can be used across various fields, such as healthcare, to support and enhance health services. An essential key feature of conversational chatbots is their ability to deliver swift and automated responses. In healthcare, these bots serve multiple purposes, including setting appointments, answering questions, and providing recommendations.
Modern-day conversational chatbots leverage artificial intelligence techniques, such as machine learning and natural language processing, to understand and respond to user inquiries effectively. This study will discuss the objectives of developing chatbot systems, the fundamental methodologies and datasets used, the primary challenges and limitations of existing works, and insights into future trends in chatbot development.
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