ReviewJournal of experimental orthopaedics2025
Artificial intelligence-driven analysis identifies arthroscopic shoulder surgery, meniscus injury and treatment, and total knee arthroplasty design biomechanics as the most commonly published topics in
Review in Journal of experimental orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Artificial intelligence in shoulder arthroplasty: latest concepts and clinical integration.Journal of orthopaedic surgery and research · 2026Review
- Digital Health and Smart Technologies in Shoulder Arthroplasty: Emerging Tools and Clinical Implications.Orthopedic research and reviews · 2026Review
- Artificial intelligence-driven analysis identifies arthroscopic shoulder surgery, meniscus injury and treatment, and total knee arthroplasty design biomechanics as the most commonly published topics inJournal of experimental orthopaedics · 2025Review
- Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology.Frontiers in pharmacology · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To utilize advanced topic modelling through the Bidirectional Encoder Representations from Transformers Topic (BERTopic) model to investigate research topics in the journal Methods: Titles and abstracts from 7886 original research articles and reviews published in Results: The BERTopic model organized 7410 publications into 33 distinct topics. From 1993 to 2023, the most frequently reported topics included arthroscopic shoulder surgery, meniscus injury and treatment, and total knee arthroplasty (TKA): design biomechanics. Between 2020 and 2023, arthroscopic shoulder surgery, TKA: design biomechanics, and TKA: alignment & kinematics were identified as increasingly popular ('hot') topics. Conversely, ankle instability, non-anterior cruciate ligament (ACL) knee ligament injuries, and ACL reconstruction: bone tunnels showed declining popularity ('cold' topics). Conclusions: This study demonstrates the efficacy of the BERTopic model in analyzing large textual data sets to identify relevant research patterns within orthopaedic literature. The results highlight BERTopic's ability to summarize thousands of articles from Level of Evidence: Level IV, systematic review.
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.