Evidence map›Paper›PMID 37397384›Full record

ArticleFrontiers in oncology2023

Evaluation of artificial intelligent breast ultrasound on lesion detection and characterization compared with hand-held ultrasound in asymptomatic women.

Bin Xu, Weidong Luo, Xin Chen, Yiping Jia, Mengyuan Wang, Lulu Tian, Yi Liu, Bowen Lei, Jiayuan Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Bin XuDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Weidong LuoDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Xin ChenDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Yiping JiaDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Mengyuan WangDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Lulu TianDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Yi LiuDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Bowen LeiDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
Jiayuan LiDepartment of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: To compare the accuracy of Artificial Intelligent Breast Ultrasound (AIBUS) with hand-held breast ultrasound (HHUS) in asymptomatic women and to offer recommendations for screening in regions with limited medical resources. Methods: 852 participants who underwent both HHUS and AIBUS were enrolled between December 2020 and June 2021. Two radiologists, who were unaware of the HHUS results, reviewed the AIBUS data and scored the image quality on a separate workstation. Breast imaging reporting and data system (BI-RADS) final recall assessment, breast density category, quantified lesion features, and examination time were evaluated for both devices. The statistical analysis included McNemar's test, paired t-test, and Wilcoxon test. The kappa coefficient and consistency rate were calculated in different subgroups. Results: Subjective satisfaction with AIBUS image quality reached 70%. Moderate agreements were found between AIBUS with good quality images and HHUS for the BI-RADS final recall assessment ( Conclusion: Moderate agreement was obtained for the description of the BI-RADS final recall assessment and breast density category. With image quality comparable to that of HHUS, AIBUS was superior for the efficiency of primary screening.

Indexed as

automated breast ultrasoundbreastbreast lesionhand-held breast ultrasoundscreening

Identifiers

PMID37397384
PMCPMC10311017

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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.