Advancing digital mental healthcare: the role of artificial intelligence and natural language processing in powering medical chatbots for future healthcare interventions

Abstract

INTRODUCTION: The fusion of Artificial Intelligence and Machine Learning in the context of healthcare informatics has opened up revolutionary improvements with the help of applications in Artificial Intelligence-powered NLP (Natural Language Processing). The algorithms are designed and developed by artificial intelligence and are utilized to conduct comprehensive analysis within medical data, and they improve medical decisions. Within this revolutionary scenario, the mental healthcare (MHC) chatbots based on NLP bring about revolutionary improvements in processing large-scale complex medical information. AREAS COVERED: In this narrative review, the structured literature review has been carried out on diversified databases like Scopus, PubMed, Web of Science, IEEE Xplore, and Google Scholar for published articles during the time frame of 2017 to 2025. The framework, algorithms, performance measures, and SWOT analysis of NLP-based medical chatbots are examined to showcase the capabilities with existing limitations in revolutionizing healthcare informatics. EXPERT OPINION: The NLP chatbots help facilitate real-time therapy sessions, support the scheduling of appointments, and generate timely responses more easily. However, with a structured architectural framework provision to address the safety and effectiveness concerns, these chatbots can be more responsible in real-world applications.

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