Evidence map›Paper›PMID 35754091›Full record

SynthesisEuropean radiology2022

Diagnostic accuracy and potential covariates of artificial intelligence for diagnosing orthopedic fractures: a systematic literature review and meta-analysis.

Xiang Zhang, Yi Yang, Yi-Wei Shen, Ke-Rui Zhang, Ze-Kun Jiang, Li-Tai Ma, Chen Ding, Bei-Yu Wang, Yang Meng, Hao Liu

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  10. Advances in Artificial Intelligence for Wrist Joint Injury Diagnosis.International journal of medical sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xiang ZhangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Yi YangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Yi-Wei ShenDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Ke-Rui ZhangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Ze-Kun JiangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000, China.
Li-Tai MaDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Chen DingDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Bei-Yu WangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Yang MengDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China.
Hao LiuDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, No. 37 Guo Xue Rd, Chengdu, 610041, China. liuhao6304@126.com.ORCID http://orcid.org/0000-0002-2992-6232

Funding

Popularization and Application Project of the Sichuan Provincial Health Commission 21PJ037
6 · The paper itself

Abstract

objectivesTo systematically quantify the diagnostic accuracy and identify potential covariates affecting the performance of artificial intelligence (AI) in diagnosing orthopedic fractures.

methodsPubMed, Embase, Web of Science, and Cochrane Library were systematically searched for studies on AI applications in diagnosing orthopedic fractures from inception to September 29, 2021. Pooled sensitivity and specificity and the area under the receiver operating characteristic curves (AUC) were obtained. This study was registered in the PROSPERO database prior to initiation (CRD 42021254618).

resultsThirty-nine were eligible for quantitative analysis. The overall pooled AUC, sensitivity, and specificity were 0.96 (95% CI 0.94-0.98), 90% (95% CI 87-92%), and 92% (95% CI 90-94%), respectively. In subgroup analyses, multicenter designed studies yielded higher sensitivity (92% vs. 88%) and specificity (94% vs. 91%) than single-center studies. AI demonstrated higher sensitivity with transfer learning (with vs. without: 92% vs. 87%) or data augmentation (with vs. without: 92% vs. 87%), compared to those without. Utilizing plain X-rays as input images for AI achieved results comparable to CT (AUC 0.96 vs. 0.96). Moreover, AI achieved comparable results to humans (AUC 0.97 vs. 0.97) and better results than non-expert human readers (AUC 0.98 vs. 0.96; sensitivity 95% vs. 88%).

conclusionsAI demonstrated high accuracy in diagnosing orthopedic fractures from medical images. Larger-scale studies with higher design quality are needed to validate our findings. KEY POINTS: • Multicenter study design, application of transfer learning, and data augmentation are closely related to improving the performance of artificial intelligence models in diagnosing orthopedic fractures. • Utilizing plain X-rays as input images for AI to diagnose fractures achieved results comparable to CT (AUC 0.96 vs. 0.96). • AI achieved comparable results to humans (AUC 0.97 vs. 0.97) but was superior to non-expert human readers (AUC 0.98 vs. 0.96, sensitivity 95% vs. 88%) in diagnosing fractures.

Indexed as

Fractures, BoneOrthopedicsArtificial IntelligenceHumansMulticenter Studies as TopicROC CurveSensitivity and SpecificityArtificial intelligenceFractures, boneMeta-analysis

Identifiers

PMID35754091

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.