Evidence map›Paper›PMID 37969190›Full record

ArticleAmerican journal of translational research2023

Artificial intelligence technology enhances the performance of shear wave elastography in thyroid nodule diagnosis.

Jingmei Tuo, Xiaojuan Si, Heqin Song

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 39% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
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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

3 authors at 1 institution in 1 country.

Jingmei TuoDepartment of Ultrasound Medicine, Zhangjiakou First Hospital Zhangjiakou 330098, Hebei, China.
Xiaojuan SiDepartment of Ultrasound Medicine, Zhangjiakou First Hospital Zhangjiakou 330098, Hebei, China.
Heqin SongDepartment of Laboratory Medicine, Zhangjiakou First Hospital Zhangjiakou 330098, Hebei, China.
Hebei North University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the diagnostic value of Artificial Intelligence (AI) in thyroid nodules diseases.

methodsThis study included 100 patients (100 nodules - 23 benign; 77 malignant) who underwent shear wave elastography (SWE) and AI imaging of nodules prior to biopsy and/or surgery in Zhangjiakou First Hospital from January 2021 to December 2021. The image diagnostic value of AI was analyzed.

resultsAmong the 100 patients, there were 77 malignant nodules (77%) and 23 benign nodules (23%). Papillary thyroid carcinoma accounted for 94.8% (74/77) of the malignant nodules, and nodular goiter accounted for 100% of the benign nodules. The overall detection rate of AI+SWE was higher than that of SWE alone (P < 0.05). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of AI+SWE were all higher than those of SWE only (P < 0.05). The ROC curve results showed that the area under the curve of AI+SWE in the diagnosis of thyroid nodules was 0.903. This was higher than that of SWE (P < 0.05).

conclusionSWE+AI is effective in the diagnosis of thyroid nodules, and its sensitivity and specificity are better than those of SWE only.

Indexed as

Artificial intelligenceshear wave elastographythyroid nodules

Identifiers

PMID37969190
PMCPMC10641343
OpenAlexW4388737316

What OpenQuestion holds

Textmetadata
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.