ReviewOrthopadie (Heidelberg, Germany)2022
[Artificial intelligence in orthopaedic and trauma surgery imaging].
Review in Orthopadie (Heidelberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Review
- Artificial intelligence in radiology and diagnostic imaging.Bioinformation · 2025Article
- Diagnostic Value of Hounsfield Units for Osteoporotic Thoracolumbar Vertebral Non-Compression Fractures in Elderly Patients with Low-Energy Injuries.International journal of general medicine · 2024Article
- Artificial Intelligence, the Digital Surgeon: Unravelling Its Emerging Footprint in Healthcare - The Narrative Review.Journal of multidisciplinary healthcare · 2024Review
- The Changing Environment in Postgraduate Education in Orthopedic Surgery and Neurosurgery and Its Impact on Technology-Driven Targeted Interventional and Surgical Pain Management: Perspectives from Europe, Latin America, Asia, and The United States.Journal of personalized medicine · 2023Article
- Decade-long insights into AI for orthopedic rehabilitation mapping research networks and future trajectories.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is playing an increasing role in radiological imaging in orthopaedics and trauma surgery. The algorithms available to date are predominantly used in the detection of (occult) fractures and in length and angle measurements in conventional X‑ray images. However, current AI solutions also enable the analysis and pattern recognition of CT datasets, e.g. in the detection of rib or vertebral body fractures. A special application is EOS™ (ATEC Spine Group, Paris, France), which enables a 3‑D simulation of the axial skeleton and semi-automatic length and angle calculations based on a digital 2‑D X‑ray image. In this paper, the current spectrum of AI applications for orthopaedics and trauma surgery is presented and discussed.
Indexed as
Identifiers
35980460What 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.