ArticlePerspectives in health information managemen2009
Translational bioinformatics and healthcare informatics: computational and ethical challenges.
Article in Perspectives in health information managemen, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Incorporation of personal single nucleotide polymorphism (SNP) data into a national level electronic health record for disease risk assessment, part 1: an overview of requirements.JMIR medical informatics · 2014Article
- Recent development and biomedical applications of probabilistic Boolean networks.Cell communication and signaling : CCS · 2013Review
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
Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs). In this paper, we explore the computational and ethical challenges that emanate from the intersection of bioinformatics and healthcare informatics research. We describe the current situation of the EHR and its capabilities to store clinical and genetic data and then discuss the Genetic Information Nondiscrimination Act. Finally, we posit that the synergy obtained from the collaborative efforts between the genomics, clinical, and healthcare disciplines has potential to enhance and promote faster and more advanced breakthroughs in healthcare.
Indexed as
Identifiers
20169020PMC2804463What 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.