Artificial Intelligence (AI) in Perioperative Medicine

Abstract

The excitement around AI is palpable in the hallways of hospitals everywhere.This is somewhat justified, and recently the availability of this technology, in large language models (LLM's), such as ChatGPT, has heralded a new era in human endeavor.However, it's role may have been overemphasized, leaving many uncertain about the future workplace and their roles in it.Perioperative medicine is an emerging field, situated within the overlapping realms of surgery, anaesthesia, and critical care.Its exact boundaries are not yet clearly defined, making it difficult to classify it as a stand-alone specialty.The confluence of AI and perioperative medicine offers a unique opportunity to create integrated workflows and innovative tools which may accelerate the novel and perhaps practice enhancing aspects of AI more rapidly in this area.This may be harder to achieve in more established specialties due to ingrained behaviors and practices.(1)Artificial intellegence's role in the perioperative space includes areas such as data analytics for early warning systems, image analysis, the fascinating field of radiomics, robotic surgery assistance, and large data analysis to aid decision support systems.These can help optimize patient care and improve safety by recognizing inefficient and potentially dangerous patterns, especially in electronic medical record platforms.(2-5)Artificial intellegence also assists in risk assessment, risk mitigation planning, and patient communication.According to some assessments even outperforming physicians in empathy and effectiveness.It is this relational aspect of care where I feel the perioperative clinician can already see the benefits of the utilization of LLM's.The use of LLM's for generating layperson summaries, motivation letter writing, and protocol design is already in use in many perioperative practices.(6,7)From anaesthsia to orthopedic surgery to radiological imaging, and numerous other fields, there has been a recent marked escalation in the number of papers and metanalyses on the role and efficacy of AI in the healthcare environment.

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