ReviewBiological research for nursing2020
The State of Data Science in Genomic Nursing.
Review in Biological research for nursing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- A multidisciplinary perspective on advancing genomic nursing in Portugal: roles, barriers and system-level solutions.Journal of community genetics · 2026Article
- Article
- Advancing Nursing Research Through Interactive Data Visualization With R Shiny.Biological research for nursing · 2023Article
- Nursing science as a federally-recognized STEM degree: A call to action for the United States with global implications.International journal of nursing studies advances · 2022Article
- Multi-Staged Data-Integrated Multi-Omics Analysis for Symptom Science Research.Biological research for nursing · 2021Article
- Application of Predictive Analytics in Pregnancy, Birth, and Postpartum Nursing Care.MCN. The American journal of maternal child nursingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Nurse scientists are generating, acquiring, distributing, processing, storing, and analyzing greater volumes of complex omics data than ever before. To take full advantage of big omics data, to address core biological questions, and to enhance patient care, however, genomic nurse scientists must embrace data science. Intended for readership with limited but expanding data science knowledge and skills, this article aims to provide a brief overview of the state of data science in genomic nursing. Our goal is to introduce key data science concepts to genomic nurses who participate at any stage of the data science lifecycle, from research patient recruitment to data wrangling, preprocessing, and analysis to implementation in clinical practice to policy creation. We address three major components in this review: (1) fundamental terminology for the field of genomic nursing data science, (2) current genomic nursing data science research exemplars, and (3) the spectrum of genomic nursing data science roles as well as education pathways and training opportunities. Links to helpful resources are included throughout the article.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.