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Comparing Manual and ChatGPT Deep Research on Systematic Search and Selection in the PubMed Database on the Topic of
Bulcsú Bencze1, Alwin Sokolowski2, Jae-Hyun Lee3
1Department of Prosthodontics, Semmelweis University, Budapest, Hungary.
Introduction:
Dental implantology has seen rapid technological advancements, with artificial intelligence (AI) increasingly integrated into diagnostic, planning, and surgical processes. The release of chat-generative pretrained transformer (ChatGPT) and its subsequent updates, including the deep research function, presents opportunities for AI-assisted systematic reviews. However, its efficacy compared to traditional manual research has not been researched.
Materials And Methods:
A systematic review was conducted on May 6, 2025, to evaluate recent innovations in dental implantology and AI. Two parallel searches were performed: one using ChatGPT 4.1's deep research tool in the PubMed database and another manual PubMed search by two independent reviewers. Both searches used identical keywords and Boolean operators targeting studies from 2020 to 2025. Inclusion criteria were peer-reviewed studies related to implant design, osseointegration, guided placement, and other predefined outcomes.
Results:
The manual search identified 124 articles, of which 23 met the inclusion criteria. ChatGPT retrieved 114 articles, selected 13 for inclusion, yet only included 11 in its synthesis. Two cited articles by the AI software were nonexistent, and numerous relevant studies were not retrieved, whereas the remaining articles were correct and found by manual search as well. ChatGPT had high specificity (98%) and low sensitivity (47.8%), with a statistically significant difference compared to manual search and selection.
Discussion:
AI tools like ChatGPT show promise in literature search, synthesis, and assistance, especially in improving readability and identifying trending topics in science. Nevertheless, the current state of deep research function lacks the reliability required for conducting systematic reviews due to issues such as made-up references and missed articles. The results highlight the need for human supervision and improved safeguards.
Conclusions:
ChatGPT's deep research function can support, but not replace manual systematic search and selection. It offers substantial benefits in writing support and preliminary synthesis due to acceptable accuracy, but limitations in reliability and low sensitivity (47.8%) require cautious use and transparent reporting of any AI involvement in scientific research.
