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Early predicting tribocorrosion rate of dental implant titanium materials using random forest machine learning models

Tribology International(2023)10.1016/j.triboint.2023.108735Source: DataRank Database

Early predicting tribocorrosion rate of dental implant titanium materials using random forest machine learning models is a research paper published in Tribology International (2023). On theSindex it has a DataRank of 0. It has been cited 16 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access16 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (4 grants)Impact (FWCI 4.49)OA: greenTopics (22)IDs (PubMed, PMC, 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 (6)

Valentim Adelino Ricardo Barão ORCID,Didem Ozevin ORCID,Cortino Sukotjo ORCID,Srinivasa Pai P,Mathew T. Mathew ORCID

Live enrichment

PubMed:37720691 PMC:PMC10503681 OpenAlex:https://openalex.org/W4382052053

CNPq

Grant: 307471/2021-7

NIH

Grant: R01 DE031832

FAPESP

Grant: 2020/05231-4

NIAMS NIH HHS

Grant: R56 AR070181

FWCI

4.49

Citation Percentile

1.0%

Citation Trend

2023

2024

2025

2026

greenLicense: http://www.elsevier.com/open-access/userlicense/1.0/

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10503681/pdf/nihms-1914628.pdf

BRONZEhttps://www.sciencedirect.com/science/article/am/pii/S0301679X23005236

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10503681/pdf/nihms-1914628.pdf

publisherhttps://api.elsevier.com/content/article/PII:S0301679X23005236?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0301679X23005236?httpAccept=text/plain

Fields of Study

Orthopaedic implants and arthroplastyDental Radiography and ImagingDental Implant Techniques and OutcomesMedicineEngineeringMaterials Science

Keywords

TribocorrosionDental implantMaterials scienceCorrosionZirconiumRandom forestTitaniumImplantMachine learningMetallurgyComputer scienceMedicineSurgeryElectrochemistryDental ImplantsHealth Monitoring

Sustainable Development Goals

SDG 0: Life in Land