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"Predictive Chronic Wound Monitoring Protocol for Healing Assessment via Intelligent Biosensing Technology and Machine Learning"

Biomedical Journal of Scientific & Technical Research(2022)10.26717/bjstr.2022.46.007429Source: DataRank Database

"Predictive Chronic Wound Monitoring Protocol for Healing Assessment via Intelligent Biosensing Technology and Machine Learning" is a research paper published in Biomedical Journal of Scientific & Technical Research (2022). On theSindex it has a DataRank of 0. It has been cited 2 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)Impact (FWCI 0.25)OA: goldTopics (17)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (1)

Teresa J. Kelechi ORCID

Live enrichment

PubMed:19965766 OpenAlex:https://openalex.org/W4382500873

National Institutes of Health

Grant: 3UL1TR001450-06S1

South Carolina Clinical & Translational Research Institute (SCTR)

FWCI

0.25

Citation Percentile

0.6%

Citation Trend

2025

goldLicense: cc-by

journalhttps://biomedres.us/pdfs/BJSTR.MS.ID.007429.pdf

GOLDhttps://biomedres.us/pdfs/BJSTR.MS.ID.007429.pdf

publisherhttps://biomedres.us/pdfs/BJSTR.MS.ID.007429.pdf

journalhttps://doi.org/10.26717/bjstr.2022.46.007429

Fields of Study

Diabetic Foot Ulcer Assessment and ManagementMedicineEngineeringComputer Science0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Wound healingMedicineChronic woundProtocol (science)PopulationArtificial intelligenceIntensive care medicineMachine learningSurgeryComputer sciencePathology

Sustainable Development Goals

SDG 0: Good health and well-being