713 Conversational Artificial Intelligence in Plastic Surgery: A Systematic Review

Abstract

Abstract Aim Rapid advancements in technology have paved the way for the use of artificially intelligent (AI) conversational agents. Conversational AI has the potential to transform patient pathways, with increasing use in triage, virtual consultations and post-operative care. The aim of this systematic review is to evaluate the scale and scope of conversational AI within Plastic Surgery. Method Following PRISMA guidelines, a systematic review of PubMed, Embase, PsychInfo, Scopus and Google Scholar using COVIDENCE software, was performed on applications of conversational AI within Plastic Surgery. Assessment of quality and risk of bias was performed for all studies. Results Overall, 479 studies were captured by the search and four were included in the final analysis. Three independent reviewers screened s and full texts with a kappa score for interrater reliability of 1.0. Uses of conversational AI included ChatBots (n=2), virtual assistants (n=1) and machine learning models (n=1). Conversational AI was used in various settings including flap monitoring, outpatient management of paediatric burns and general plastics in addition to frequently asked questions (FAQS), and analysis of conversations to promote quality improvement. Only two studies included an evaluation of end-user satisfaction and accuracy. Risk of bias was high, and level of evidence was low. Conclusions At present conversational AI has a variety of uses within Plastic Surgery ranging from ChatBots supporting doctors and responding to patient queries, to researching quality improvement strategies. However, conversational AI could be further utilised within Plastic Surgery and further study and innovation are required to fully leverage its potential.

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