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Dynamic modeling and system identification of user engagement in mHealth interventions using a Bayesian approach for missing data imputation

Control Engineering Practice(2025)10.1016/j.conengprac.2025.106460Source: DataRank Database

Dynamic modeling and system identification of user engagement in mHealth interventions using a Bayesian approach for missing data imputation is a research paper published in Control Engineering Practice (2025). On theSindex it has a DataRank of 0.

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)Impact (FWCI 0.00)OA: greenTopics (20)IDs (PubMed, OpenAlex)

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 (7)

Steven De La Torre ORCID,Benjamin M. Marlin ORCID,Misha Pavel ORCID,Predrag Klasnja ORCID,Donna Spruijt‐Metz ORCID

Live enrichment

PubMed:40727918 OpenAlex:https://openalex.org/W4411772045

National Institute of Biomedical Imaging and Bioengineering

Grant: 1P41EB028242

NIBIB NIH HHS

Grant: P41 EB028242

NCI NIH HHS

Grant: U01 CA229445

FWCI

0.00

Citation Percentile

0.1%

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

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12290899/

publisherhttps://api.elsevier.com/content/article/PII:S0967066125002229?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0967066125002229?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.conengprac.2025.106460

Fields of Study

Mental Health Research TopicsDigital Mental Health InterventionsBehavioral Health and Interventions

Keywords

Imputation (statistics)Missing datamHealthComputer sciencePsychological interventionIdentification (biology)Bayesian probabilityData miningDynamic Bayesian networkData scienceMachine learningPsychologyArtificial intelligenceBayesian methodsControl-oriented behavioral interventionsdynamic modeling for social science applicationseHealth