The Utility of Artificial Intelligence for Systematic Reviews and Boolean Query Formulation and Translation

作者：Leonardo Alaniz, Cindy Vu, Miles J. Pfaff · 发表于：Plastic & Reconstructive Surgery Global Open · 年份：2023 · DOI：10.1097/gox.0000000000005339 · 被引用次数：24 · 研究领域：Artificial Intelligence in Healthcare and Education、COVID-19 diagnosis using AI、Radiomics and Machine Learning in Medical Imaging

The formulation of precise search strings and syntax translation between databases is pivotal to a successful systematic review. By using the subscription-based ChatGPT,1 researchers can harness natural language processing to generate refined search strings and Boolean queries, streamlining the process and enhancing the accuracy of the systematic review. Although there are few publications addressing ChatGPT’s utility as a general research aid,2–4 there are no reports on how ChatGPT-4 can be leveraged as a collaborative tool to collectively build a search string and translate Boolean queries into other database languages. We conducted a mock systematic review describing the utility of augmented and virtual reality systems for preoperative planning in craniosynostosis surgery. We compiled a list of medical subject heading [MeSH] terms and keywords relevant to the research question. Next, we incorporated ChatGPT-4 as a Boolean query aid to formulate an optimal PubMed search string (Table 1). Its first task was to analyze our study aim and provide additional databases to query for relevant articles. It then assisted us in refining our list of relevant MeSH terms and keywords for PubMed. Although it successfully added terms and enhanced our term list, researchers should still cross-reference MeSH terms with the database given ChatGPT-4’s training cutoff date of 2021. (See table 1, Supplemental Digital Content 1, which shows a comprehensive list of original and modified MeSH terms...