Evidence map›Paper›PMID 34873414›Full record

ArticleComputational and mathematical methods in medicine2021

Image Processing for mHealth-Based Approach to Detect the Local Tissue Inflammation in Cutaneous Leishmaniasis: A Proof of Concept Study.

Hermali Silva, Kalaivani Chellappan, Nadira Karunaweera

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 20% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Diagnostic Tools for Cutaneous Leishmaniasis Caused byDiagnostics (Basel, Switzerland) · 2023
    Review
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.

Hermali SilvaDepartment of Parasitology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka.ORCID https://orcid.org/0000-0003-2288-1294
Kalaivani ChellappanDepartment of Electrical, Electronic & Systems Engineering, Faculty of Engineering & Built Environment, National University of Malaysia, Bangi, Selangor, Malaysia.ORCID https://orcid.org/0000-0002-2618-216X
Nadira KarunaweeraDepartment of Parasitology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka.ORCID https://orcid.org/0000-0003-3985-1817
University of Colombo · LKNational University of Malaysia · MY

Funding

Epidemiology and transmission of Leishmania donovani infections in Sri Lanka and BhutanU01AI136033 · NIAID · UNIVERSITY OF COLOMBO · PI KARUNAWEERA, NADIRA DHARSHANI, ZHOU, GUOFA · 2017 to 2021
$2.0M
NIAID NIH HHS U01 AI136033
6 · The paper itself

Abstract

Skin lesions are a feature of many diseases including cutaneous leishmaniasis (CL). Ulcerative lesions are a common manifestation of CL. Response to treatment in such lesions is judged through the assessment of the healing process by regular clinical observations, which remains a challenge for the clinician, health system, and the patient in leishmaniasis endemic countries. In this study, image processing was initially done using 40 CL lesion color images that were captured using a mobile phone camera, to establish a technique to extract features from the image which could be related to the clinical status of the lesion. The identified techniques were further developed, and ten ulcer images were analyzed to detect the extent of inflammatory response and/or signs of healing using pattern recognition of inflammatory tissue captured in the image. The images were preprocessed at the outset, and the quality was improved using the CIE

Indexed as

AlgorithmsComputational BiologyHumansImage Interpretation, Computer-AssistedInflammationLeishmaniasis, CutaneousPhotographyPrincipal Component AnalysisProof of Concept StudySkin UlcerSmartphoneSri LankaTelemedicine

Identifiers

PMID34873414
PMCPMC8643237
OpenAlexW3215257371

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.