ArticleInternational journal of dentistry2025
Comparing Manual and ChatGPT Deep Research on Systematic Search and Selection in the PubMed Database on the Topic of Dental Implantology.
Article in International journal of dentistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Large language models in implant dentistry: a scoping review of applications, performance, and limitations.BMC oral health · 2026Article
- The role of artificial intelligence in the authorship of scientific articles in dentistry: ethical approaches for responsible use.Revista cientifica odontologica (Universidad Cientifica del Sur)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.