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MedReadr: Development and Evaluation of an In-Browser, Rule-Based Natural Language Processing Algorithm to Estimate the Reliability of Consumer Health Articles

Biomedicine Hub(2025)10.1159/000548163Source: DataRank Database

MedReadr: Development and Evaluation of an In-Browser, Rule-Based Natural Language Processing Algorithm to Estimate the Reliability of Consumer Health Articles is a research paper published in Biomedicine Hub (2025). On theSindex it has a DataRank of 0.

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Enrichment:OA: goldTopics (4)Linked Datasets (2)DataCite Reuse (2)IDs (PubMed, PMC)

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Authors (10)

Autumn Kim,Nikit Venishetty ORCID,Alia Codelia‐Anjum ORCID,Dean Elterman ORCID,Naeem Bhojani ORCID

Live enrichment

PubMed:41064735 PMC:PMC12503773

goldLicense: cc-by-nc

publisherhttps://doi.org/10.1159/000548163

publisherhttps://karger.com/article-pdf/doi/10.1159/000548163

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12503773

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12503773/

repositoryhttps://hdl.handle.net/1807/151056

Keywords

Internet UseConsumer Health InformationAlgorithmsInformation Literacy

Supplementary Material for: MedReadr: Development and evaluation of an in-browser, rules-based natural language processing algorithm to estimate the reliability of consumer health articles

10.6084/m9.figshare.29978308.v1Karger Publishers

Supplementary Material for: MedReadr: Development and evaluation of an in-browser, rules-based natural language processing algorithm to estimate the reliability of consumer health articles

10.6084/m9.figshare.29978308Karger Publishers