  This paper presents an analytical framework for conducting academic reviews
in the field of Healthcare Systems Engineering, employing ChatGPT, a
state-of-the-art tool among recent language models. We utilized 9,809 abstract
paragraphs from conference presentations to systematically review the field.
The framework comprises distinct analytical processes, each employing tailored
prompts and the systematic use of the ChatGPT API. Through this framework, we
organized the target field into 11 topic categories and conducted a
comprehensive analysis covering quantitative yearly trends and detailed
sub-categories. This effort explores the potential for leveraging ChatGPT to
alleviate the burden of academic reviews. Furthermore, it provides valuable
insights into the dynamic landscape of Healthcare Systems Engineering research.
