Evidence map›Paper›PMID 31348028›Full record

ArticleChinese medical journal2019

Update on thyroid ultrasound: a narrative review from diagnostic criteria to artificial intelligence techniques.

Xiao-Wen Liang, Yong-Yi Cai, Jin-Sui Yu, Jian-Yi Liao, Zhi-Yi Chen

Open access · goldAbstract read
In one paragraph

Article in Chinese medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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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

5 authors at 1 institution in 2 countries.

Xiao-Wen LiangDepartment of Ultrasound Medicine, Laboratory of Ultrasound Medicine and Artificial Intelligence, Experimental Center of Liwan Hospital, The Third Affiliated Hospital of Guangzhou Medical University, The Liwan Hospital of the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510000, China.
Yong-Yi Cai
Jin-Sui Yu
Jian-Yi Liao
Zhi-Yi Chen
Information Today (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveUltrasound imaging is well known to play an important role in the detection of thyroid disease, but the management of thyroid ultrasound remains inconsistent. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. This study reviewed the global guidelines of thyroid ultrasound and analyzed their common characteristics for basic clinical screening. Advances in the application of a combination of thyroid ultrasound and artificial intelligence (AI) were also presented. DATA SOURCES: An extensive search of the PubMed database was undertaken, focusing on research published after 2001 with keywords including thyroid ultrasound, guideline, AI, segmentation, image classification, and deep learning. STUDY SELECTION: Several types of articles, including original studies and literature reviews, were identified and reviewed to summarize the importance of standardization and new technology in thyroid ultrasound diagnosis.

resultsUltrasound has become an important diagnostic technique in thyroid nodules. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. In the standardization, since there are no global consensus exists, common characteristics such as a multi-feature diagnosis, the performance of lymph nodes, explicit indications of fine needle aspiration, and the diagnosis of special populations should be focused on. Besides, evidence suggests that AI technique has a good effect on the unavoidable limitations of traditional ultrasound, and the combination of diagnostic criteria and AI may lead to a great promotion in thyroid diagnosis.

conclusionStandardization and development of novel techniques are key factors to improving thyroid ultrasound, and both should be considered in normal clinical use.

Indexed as

Artificial IntelligenceDeep LearningHumansThyroid GlandThyroid Nodule

Identifiers

PMID31348028
PMCPMC6708700
OpenAlexW2965770401

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.