ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2023
[Value of artificial intelligence in the improvement of diagnostic consistency of radiology residents].
Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Acupoints Compatibility Rules of Acupuncture for Functional Gastrointestinal Disorders Based on Data Mining Technology: A Systematic Review.Iranian journal of public health · 2025Review
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
objectiveTo explore the value of artificial intelligence (AI) in improving the detection rate of traumatic rib fractures by radiologist residents and the consistency among different readers.
methodsChest CT images of 393 patients with acute trauma from China-Japan Union Hospital of Jilin University (hospital 02) and Shanghai Ninth People' s Hospital (hospital 03) were collected in this research. The consensus achieved by three radiology experts was regarded as the reference standard. All the images assigned to three hospitals: Peking University First Hospital (hospital 01), hospital 02 and hospital 03, and were then randomly divided into two groups (group A and group B: group A included 197 patients, and group B included 196 patients). Each group was read by one radiologist resident from each hospital for rib fracture detection. Each case was read twice by the same radiologist, with and without the assistance of the AI ["radiologist-only" reading and "radiologist + AI" reading]. The detection rates of different types of rib fractures (displaced fractures and occult fractures) were compared between "radiologist-only" reading and "radiologist + AI" reading. The consistencies of different radiologists with different reading methods were evaluated.
resultsThe detection rates of displaced rib fractures and occult rib fractures by "radiologist + AI" reading were significantly higher than those read by "radiologist-only" reading (94.56%
conclusionAI software can be used to automatically detect suspected rib fracture lesions, which helps to improve the detection rate of fracture lesions and the consistency among different readers.
Indexed as
Identifiers
37534650PMC10398781What 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.