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Deep imputation of missing values in time series health data: A review with benchmarking

Journal of Biomedical Informatics(2023)10.1016/j.jbi.2023.104440Source: DataRank Database

Deep imputation of missing values in time series health data: A review with benchmarking is a research paper published in Journal of Biomedical Informatics (2023). On theSindex it has a DataRank of 0. It has been cited 90 times.

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Open Access90 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 12.47)OA: greenTopics (46)IDs (PubMed, PMC, OpenAlex)Annotations (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 (2)

Manar D. Samad ORCID,Maksims Kazijevs

Live enrichment

PubMed:37429511 PMC:PMC10529422 OpenAlex:https://openalex.org/W4383621844

NLM NIH HHS

Grant: R15 LM013569

National Institutes of Health

Grant: 1R15LM013569-01

Optimizing the Utility of Large Electronic Health Records Data in Data-Driven Health Research

National Library of Medicine

National Institutes of Health

FWCI

12.47

Citation Percentile

1.0%

Citation Trend

2023

2024

2025

2026

greenLicense: other-oa

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10529422/pdf/nihms-1916143.pdf

publisherhttps://api.elsevier.com/content/article/PII:S1532046423001612?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1532046423001612?httpAccept=text/plain

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/10529422

Fields of Study

Machine Learning in HealthcareBlood Pressure and Hypertension StudiesStatistical Methods in Epidemiology02 engineering and technology03 medical and health sciences0302 clinical medicine0202 electrical engineering, electronic engineering, information engineeringBenchmarkingResearch DesignTime FactorsCross-Sectional StudiesSurveys and Questionnaires

MeSH Terms

Cross-Sectional StudiesSurveys and QuestionnairesResearch DesignTime FactorsBenchmarking

Keywords

Missing dataImputation (statistics)BenchmarkingComputer scienceData miningMultivariate statisticsDeep learningTime seriesData qualityStatisticsArtificial intelligenceMachine learningMathematicsMultivariate DataElectronic Health RecordsSensor DataMissing Value ImputationDeep Neural NetworkLongitudinal ImputationCross-sectional ImputationFOS: Computer and information sciencesComputer Science - Machine LearningTime FactorsComputer Science - Artificial IntelligenceMachine Learning (cs.LG)Cross-Sectional StudiesArtificial Intelligence (cs.AI)Research DesignSurveys and Questionnaires

Deep imputation of missing values in time series health data: A review with benchmarking

FAIR Checklist

Authors (2)

Funding (4 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)