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A Reproducible Python-Based Computational Pipeline for Real-Time Ingestion, Advanced Analysis, and Dynamic Reporting of Public Health Data: A Systems Validation Study

Cureus(2026)10.7759/cureus.103008Source: DataRank Database

A Reproducible Python-Based Computational Pipeline for Real-Time Ingestion, Advanced Analysis, and Dynamic Reporting of Public Health Data: A Systems Validation Study is a research paper published in Cureus (2026). On theSindex it has a DataRank of 0.

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Enrichment:OA: goldTopics (7)IDs (PubMed, PMC)Annotations (1)

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Findable (1/2)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (4)

Chaitra CM,Arjun B,Ananthakrishnan M,Pavan Kumar Krishnapur

Live enrichment

PubMed:41798472 PMC:PMC12966939

Influential Citations

goldLicense: cc-by

publisherhttps://www.cureus.com/articles/449538-a-reproducible-python-based-computational-pipeline-for-real-time-ingestion-advanced-analysis-and-dynamic-reporting-of-public-health-data-a-systems-validation-study.pdf

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12966939/

Europe_PMChttps://europepmc.org/articles/PMC12966939

Europe_PMChttps://europepmc.org/articles/PMC12966939?pdf=render

Fields of Study

MedicineComputer Science

Keywords

BioinformaticsPublic Health InformaticsWorkflow AutomationPython ProgrammingData Managment

A Reproducible Python-Based Computational Pipeline for Real-Time Ingestion, Advanced Analysis, and Dynamic Reporting of Public Health Data: A Systems Validation Study

FAIR Checklist

Authors (4)

Impact

Open Access

Topics

Annotations (Europe PMC)