Evidence map›Paper›PMID 37724302›Full record

ReviewMedical review (2021)2021

Digital tongue image analyses for health assessment.

Jiacheng Xie, Congcong Jing, Ziyang Zhang, Jiatuo Xu, Ye Duan, Dong Xu

Abstract readReview
In one paragraph

Review in Medical review (2021), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

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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

6 authors.

Jiacheng XieDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.
Congcong JingSchool of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Ziyang ZhangDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.
Jiatuo XuSchool of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Ye DuanChristopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Dong XuDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.ORCID https://orcid.org/0000-0002-4809-0514

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese Medicine (TCM), as an effective alternative medicine, utilizes tongue diagnosis as a major method to assess the patient's health status by examining the tongue's color, shape, and texture. Tongue images can also give the pre-disease indications without any significant disease symptoms, which provides a basis for preventive medicine and lifestyle adjustment. However, traditional tongue diagnosis has limitations, as the process may be subjective and inconsistent. Hence, computer-aided tongue diagnoses have a great potential to provide more consistent and objective health assessments. This paper reviewed the current trends in TCM tongue diagnosis, including tongue image acquisition hardware, tongue segmentation, feature extraction, color correction, tongue classification, and tongue diagnosis system. We also present a case of TCM constitution classification based on tongue images.

Indexed as

computerized diagnosisimage analysismachine learningmobile apptongue diagnosistraditional Chinese medicine

Identifiers

PMID37724302
PMCPMC10388765

What OpenQuestion holds

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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.