Applying ChatGPT and AI‐Powered Tools to Accelerate Evidence Reviews

Bibliographic Data

ID23039495
AuthorsKien Nguyen‐trung (0000-0002-1782-7405, Sustainable Development Institute, corresponding author), Alexander Saeri (0000-0001-9254-0300, READ Global), Stefan Kaufman (0000-0001-7973-3845, Sustainable Development Institute)
EditorsVictor Geraedts
Year2024
Volume2024
Issue1
Publication date2024-01-01
Open AccessYes
TypeARTICLE
VenueHuman Behavior and Emerging Technologies (JOURNAL)
Journal identifiersISSN: 2578-1863 • E-ISSN: 2578-1863
PublisherWiley (PUBLISHER • GB)
DOI10.1155/2024/8815424
OpenAlexW4405096679
LanguageEN
Citations received5
References cited22

Artificial intelligence (AI) tools have been used to improve the productivity of evidence review and synthesis since at least 2016, with EPPI‐Reviewer and Abstrackr being two prominent examples. However, since the release of ChatGPT by OpenAI in late 2022, the use of generative AI for research, especially for text‐based data analysis, has exploded. In this article, we used a critical reflection approach to document and evaluate the capacity of different generative AI tools such as ChatGPT, GPT for Google Sheets and Docs, Casper AI, and ChatPDF to assist in the early stages of a rapid evidence review process. Our results demonstrate that these tools can boost research productivity in formulating search strings and screening literature, but they have some notable weaknesses, including producing inconsistent results and occasional errors. We recommend that researchers exercise caution when using generative AI technologies by designing a thorough research strategy and review protocol to ensure effective monitoring and quality control.

Data science · Artificial Intelligence in Healthcare and Education · Computer Science · COVID-19 diagnosis using AI · Radiomics and Machine Learning in Medical Imaging

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