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Machine learning‐directed electrical impedance tomography to predict metabolically vulnerable plaques

Bioengineering & Translational Medicine(2023)10.1002/btm2.10616Source: DataRank Database

Machine learning‐directed electrical impedance tomography to predict metabolically vulnerable plaques is a research paper published in Bioengineering & Translational Medicine (2023). On theSindex it has a DataRank of 0. It has been cited 19 times.

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Open Access19 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (7 grants)OA: goldTopics (13)IDs (PubMed, PMC)SDGs (1)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (19)

Shaolei Wang ORCID,Kaidong Wang ORCID,Parinaz Abiri ORCID,Zi‐Yu Huang,Junyi Yin ORCID

Live enrichment

PubMed:38193119 PMC:PMC10771559

BLRD VA

Grant: I01 BX004356

National Institute of General Medical Sciences

Grant: T32 GM008042

NHLBI NIH HHS

Grant: R01 HL118650

National Institutes of Health

Grant: R01HL149808

National Institutes of Health

Grant: 5T32GM008042-27

Medical Scientist Training Program

National Institutes of Health

Grant: 5R01HL118650-08

Electrochemical Impedance Spectroscopy to Assess Metabolically Active Plaque

National Institutes of Health

Grant: 5R01HL149808-06

Intravascular Deployment of a Wirelessly Powered Micro-Pacer

goldLicense: cc-by

publisherhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/btm2.10616

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10771559/pdf/BTM2-9-e10616.pdf

repositoryhttps://doaj.org/article/40484d6d8f84463e9bfc7f0a17bfaa6b

Europe_PMChttps://europepmc.org/articles/PMC10771559

Europe_PMChttps://europepmc.org/articles/PMC10771559?pdf=render

Keywords

AtherosclerosisMachine LearningElectrochemical Impedance SpectroscopynanomaterialsOxidized Low‐density Lipoproteinoxidized low-density lipoproteinRM1-950Chemical engineeringTP155-156Therapeutics. PharmacologyTP248.13-248.65Research ArticlesBiotechnology

Sustainable Development Goals

SDG 3: 3. Good health