Evidence map›Paper›PMID 31357633›Full record

ArticleSensors (Basel, Switzerland)2019

Novel Image Processing Method for Detecting Strep Throat (Streptococcal Pharyngitis) Using Smartphone.

Behnam Askarian, Seung-Chul Yoo, Jo Woon Chong

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 37 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

3 authors at 2 institutions in 2 countries.

Behnam AskarianDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA.
Seung-Chul YooSchool of Communication & Media, Ewha Womans University, Seoul 03760, Korea. communication@ewha.ac.kr.
Jo Woon ChongDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. J.Chong@ttu.edu.
Texas Tech University · USEwha Womans University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we propose a novel strep throat detection method using a smartphone with an add-on gadget. Our smartphone-based strep throat detection method is based on the use of camera and flashlight embedded in a smartphone. The proposed algorithm acquires throat image using a smartphone with a gadget, processes the acquired images using color transformation and color correction algorithms, and finally classifies streptococcal pharyngitis (or strep) throat from healthy throat using machine learning techniques. Our developed gadget was designed to minimize the reflection of light entering the camera sensor. The scope of this paper is confined to binary classification between strep and healthy throats. Specifically, we adopted

Indexed as

HumansImage Processing, Computer-AssistedPharyngitisPharynxSmartphoneStreptococcaceaeStreptococcal Infectionsclassificationcolor spaceimage processingsmartphonestrep throat

Identifiers

PMID31357633
PMCPMC6695774
OpenAlexW2964423478

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.