ReviewCureus2024
Bibliometric Analysis of the Role of Artificial Intelligence in Detecting Maxillofacial Fractures.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- The Orbital Destruction Intensity Classification-An Easy-to-Use, Numerical Scale for Assessing the Severity of Orbital Fractures.Journal of clinical medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Facial bone fractures are a common occurrence in trauma cases, particularly in India where road traffic accidents contribute significantly. Over the past few years, artificial intelligence (AI) has become a potent instrument to help medical professionals diagnose and treat facial fractures. This study aims to perform a bibliometric analysis, that is, a quantitative and qualitative analysis, of publications focusing on the role of AI in detecting facial bone fractures. Bibliometric analysis can be a very strong measure of research productivity and analysis of trends within a given area of research. Data were drawn from the Dimensions AI database; 58 relevant scientific articles were analyzed in this study. This bibliometric analysis aims to assess the volume of research in this area, identifying key trends, authors, institutions, and countries contributing to the literature. The Dimensions AI database was used to gather and analyze relevant data, shedding light on the research impact through indicators such as the h-index, citation counts, and publication trends. This review will depict the landscape of research work, highlighting the rising influence of the use of AI for accurate diagnostics in facial bone fractures and further detailing gaps and potential avenues of future research directed toward solutions such as standardizing datasets and clinical integration.
Indexed as
Identifiers
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.