ArticleJournal of clinical medicine2024
Impact of Deltoid Computer Tomography Image Data on the Accuracy of Machine Learning Predictions of Clinical Outcomes after Anatomic and Reverse Total Shoulder Arthroplasty.
Article in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis 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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The implementation of artificial intelligence in upper extremity surgery: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Pre-operative deltoid fatty infiltration as a predictor of outcomes after reverse total shoulder arthroplasty: a systematic review.JSES reviews, reports, and techniques · 2026Review
- Preoperative deltoid CT attenuation predicts clinical outcomes and influences treatment selection in geriatric proximal humerus fractures.Skeletal radiology · 2026Article
- Artificial intelligence-based quantitative computed tomography assessment of shoulder muscle and its association with outcomes after reverse total shoulder arthroplasty.JSES international · 2026Article
- Artificial intelligence and machine learning: an important new set of tools for clinical shoulder arthroplasty research.JSES international · 2026Review
- Artificial Intelligence Applications in Implant Positioning, Dislocation Risk Prediction, and Surgical Indications in Orthopaedic Surgery.Bioengineering (Basel, Switzerland) · 2026Review
- Refining Reverse Shoulder Arthroplasty: From Implant Design to Patient-Specific Strategy.Journal of clinical medicine · 2026Article
- Radiomic analysis of the deltoid and scapula: identification of computed tomography-image based measurements predictive of pain, motion, and function before and after shoulder arthroplasty.JSES international · 2025Article
- Sarcopenia of the deltoid as an indicator of outcome following reverse total shoulder arthroplasty: a systematic review and meta-analysis.JSES international · 2025Review
- Analysis of patients with differing short-term rates of improvement and long-term rates of decline in range of motion and after anatomic and reverse total shoulder arthroplasty.JSES international · 2025Article
- Machine learning to predict the occurrence of complications after total shoulder arthroplasty for B2-B3 glenoids.Frontiers in surgery · 2025Article
- Evolution of Stemless Reverse Shoulder Arthroplasty: Current Indications, Outcomes, and Future Prospects.Journal of clinical medicine · 2024Review
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
PubMed holds no abstract for this paper.
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.