ArticleJournal of clinical medicine2023
The Role and Efficiency of an AI-Powered Software in the Evaluation of Lower Limb Radiographs before and after Total Knee Arthroplasty.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Artificial Intelligence Applications in Medical Devices for Personalized Health Care Solutions: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Application of artificial intelligence in X-ray imaging analysis for knee arthroplasty: A systematic review.PloS one · 2025Pooled it
- Artificial intelligence in total knee arthroplasty: clinical applications and implications.Knee surgery & related research · 2025Review
- High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- Use of Artificial Intelligence on Imaging and Preoperatory Planning of the Knee Joint: A Scoping Review.Medicina (Kaunas, Lithuania) · 2025Article
- Can Artificial Intelligence Reliably and Accurately Measure Lower Limb Alignment: A Systematic Review and Meta-Analysis.The archives of bone and joint surgery · 2025Review
- Comparison of an AI-driven planning tool and manual radiographic measurements in total knee arthroplasty.Computational and structural biotechnology journal · 2025Article
- Evaluation of a deep learning software for automated measurements on full-leg standing radiographs.Knee surgery & related research · 2024Article
- Enhancing Precision and Efficiency in Knee Arthroplasty: A Comparative Analysis of Computer-Assisted Measurements with a Novel Software Tool versus Manual Measurements for Lower Leg Geometry.Journal of clinical medicine · 2023Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid evolution of artificial intelligence (AI) in medical imaging analysis has significantly impacted musculoskeletal radiology, offering enhanced accuracy and speed in radiograph evaluations. The potential of AI in clinical settings, however, remains underexplored. This research investigates the efficiency of a commercial AI tool in analyzing radiographs of patients who have undergone total knee arthroplasty. The study retrospectively analyzed 200 radiographs from 100 patients, comparing AI software measurements to expert assessments. Assessed parameters included axial alignments (MAD, AMA), femoral and tibial angles (mLPFA, mLDFA, mMPTA, mLDTA), and other key measurements including JLCA, HKA, and Mikulicz line. The tool demonstrated good to excellent agreement with expert metrics (ICC = 0.78-1.00), analyzed radiographs twice as fast (
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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.