Evidence map›Paper›PMID 32837297›Full record

ArticleArtificial life and robotics2020

Development of a camera-based remote diagnostic system focused on color reproduction using color charts.

Masato Takahashi, Ryo Takahashi, Yasuhiro Morihara, Isseki Kin, Keiko Ogawa-Ochiai, Norimichi Tsumura

Open access · bronzeAbstract read
In one paragraph

Article in Artificial life and robotics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.3field-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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 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

6 authors at 3 institutions in 1 country.

Masato Takahashi *Graduate School of Science and Engineering, Chiba University, Chiba, Japan.
Ryo Takahashi *Graduate School of Science and Engineering, Chiba University, Chiba, Japan.
Yasuhiro MoriharaBusiness Promotion & New Development Department, DIC Graphics Corporation, Tokyo, Japan.
Isseki KinSensing Corporation, Tokyo, Japan.
Keiko Ogawa-OchiaiDepartment of Japanese-Traditional (Kampo) Medicine, Kanazawa University, Kanazawa, Japan.
Norimichi TsumuraGraduate School of Engineering, Chiba University, Chiba, Japan.
Chiba University · JPDIC (Japan) · JPKanazawa University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we propose a color reproduction method using color charts to improve the color quality of a telemedicine system. Owing to the spread of COVID-19, the need for telemedicine is rapidly increasing to prevent infections more effectively. However, in practices such as traditional Japanese (Kampo) medicine, where color is used as an important examination factor, an accurate diagnosis cannot be made without adequate color reproduction. In telemedicine using a commercially available smartphone, color reproducibility may deteriorate owing to differences in the devices and lighting, which may result in a misdiagnosis. Therefore, we created a color chart that includes the colors of the human skin and tongue as a tool to help doctors identify the color of patients more accurately when conducting a telemedicine examination. Through a subjective evaluation by eight medical doctors, it was unanimously found that the proposed method is practical in terms of a color examination. The developed color chart can also be used for an automatic color correction.

Indexed as

Color-chartColor reproductionCOVID-19Remote diagnosticTelemedicine

Identifiers

PMID32837297
PMCPMC7372208
OpenAlexW3045228331

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.