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Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)(2021)10.1109/embc46164.2021.9630135Source: DataRank Database

Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets is a research paper published in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2021). On theSindex it has a DataRank of 0. It has been cited 5 times.

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Enrichment:Funding (7 grants)OA: hybridTopics (55)IDs (PubMed, PMC)SDGs (1)

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Authors (8)

Panayiotis Petousis ORCID,Tyler A. Davis,Susanne B. Nicholas,Keith C. Norris ORCID,Katherine R. Tuttle

Live enrichment

PubMed:34891747 PMC:PMC8862635

NIDDK NIH HHS

Grant: TL1 DK132768

NCATS NIH HHS

Grant: UL1 TR001881

NIBIB NIH HHS

Grant: T32 EB016640

NIMHD NIH HHS

Grant: R01 MD014712

National Institutes of Health

Grant: 3UL1TR001881-01S2

UCLA Clinical Translational Science Institute

National Institutes of Health

Grant: 5T32EB016640-08

Medical Imaging Informatics Training Grant

National Institutes of Health

Grant: 1R01MD014712-01

Prediction of Chronic Kidney Disease by Simulation Modeling to Improve the Health of Minority Populations

hybridLicense: cc-by

publisherhttps://ieeexplore.ieee.org/ielx7/9629355/9629471/09630135.pdf

publisherhttp://xplorestaging.ieee.org/ielx7/9629355/9629471/09630135.pdf?arnumber=9630135

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/8862635

https://doi.org/10.1109/embc46164.2021.9630135

https://pubmed.ncbi.nlm.nih.gov/34891747

Fields of Study

02 engineering and technology01 natural sciences0202 electrical engineering, electronic engineering, information engineering0105 earth and related environmental sciences

MeSH Terms

HumansDisease ProgressionUncertaintyResearch DesignSoftwareRenal Insufficiency, ChronicElectronic Health RecordsDatasets as Topic

Keywords

Data Science (rcdc)1.4 Methodologies and measurements (hrcs-rac)Disease Progression (mesh)610Datasets as TopicBioengineeringElectronic Health Records (mesh)46 Information and Computing Sciences (for-2020)2.5 Research design and methodologies (aetiology)Information and Computing SciencesHealth SciencesUncertainty (mesh)Machine Learning and Artificial IntelligenceElectronic Health RecordsHumansSoftware (mesh)Renal InsufficiencyChronic4609 Information Systems (for-2020)Renal Insufficiency, ChronicChronic (mesh)42 Health Sciences (for-2020)Humans (mesh)Networking and Information Technology R&D (NITRD) (rcdc)3 Good Health and Well Being (sdg)Patient Safety (rcdc)Data ScienceBioengineering (rcdc)Generic health relevance (hrcs-hc)Datasets as Topic (mesh)2.5 Research design and methodologies (aetiology) (hrcs-rac)Uncertainty1.4 Methodologies and measurementsGood Health and Well BeingNetworking and Information Technology R&D (NITRD)Research DesignDisease ProgressionResearch Design (mesh)Patient SafetyGeneric health relevanceMachine Learning and Artificial Intelligence (rcdc)SoftwareInformation Systems

Sustainable Development Goals

SDG 3: 3. Good health