ReviewGenetics in medicine : official journal of the American College of Medical Genetics2013
Some experiences and opportunities for big data in translational research.
Review in Genetics in medicine : official journal of the American College of Medical Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Paradigm shift required for translational research on the brain.Experimental & molecular medicine · 2024Review
- Extraction of Active Medications and Adherence Using Natural Language Processing for Glaucoma Patients.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- ML-MEDIC: A Preliminary Study of an Interactive Visual Analysis Tool Facilitating Clinical Applications of Machine Learning for Precision Medicine.Applied sciences (Basel, Switzerland) · 2020Article
- Antibiotic-Resistant Septicemia in Pediatric Oncology Patients Associated with Post-Therapeutic Neutropenic Fever.Antibiotics (Basel, Switzerland) · 2019Review
- Implementing Precision Medicine and Artificial Intelligence in Plastic Surgery: Concepts and Future Prospects.Plastic and reconstructive surgery. Global open · 2019Article
- Artificial Intelligence vs. Natural Stupidity: Evaluating AI readiness for the Vietnamese Medical Information System.Journal of clinical medicine · 2019Review
- Enhancing diversity to reduce health information disparities and build an evidence base for genomic medicine.Personalized medicine · 2018Article
- Mouse Injury Model of Polytrauma and Shock.Methods in molecular biology (Clifton, N.J.) · 2018Review
- Assessing the readiness of precision medicine interoperabilty: An exploratory study of the National Institutes of Health genetic testing registry.Journal of innovation in health informatics · 2017Article
- TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.Scientific reports · 2017Article
- Orchestrating differential data access for translational research: a pilot implementation.BMC medical informatics and decision making · 2017Article
- Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017Review
- -Omic and Electronic Health Record Big Data Analytics for Precision Medicine.IEEE transactions on bio-medical engineering · 2017Review
- A Framework for Data Quality Assessment in Clinical Research Datasets.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams.Briefings in bioinformatics · 2017Article
- Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution.Journal of biomedical informatics · 2016Article
- Merging Electronic Health Record Data and Genomics for Cardiovascular Research: A Science Advisory From the American Heart Association.Circulation. Cardiovascular genetics · 2016Article
- Integrating "big data" into surgical practice.Surgery · 2016Review
- SeqFeatR for the Discovery of Feature-Sequence Associations.PloS one · 2016Article
- The future of murine sepsis and trauma research models.Journal of leukocyte biology · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Health care has become increasingly information intensive. The advent of genomic data, integrated into patient care, significantly accelerates the complexity and amount of clinical data. Translational research in the present day increasingly embraces new biomedical discovery in this data-intensive world, thus entering the domain of "big data." The Electronic Medical Records and Genomics consortium has taught us many lessons, while simultaneously advances in commodity computing methods enable the academic community to affordably manage and process big data. Although great promise can emerge from the adoption of big data methods and philosophy, the heterogeneity and complexity of clinical data, in particular, pose additional challenges for big data inferencing and clinical application. However, the ultimate comparability and consistency of heterogeneous clinical information sources can be enhanced by existing and emerging data standards, which promise to bring order to clinical data chaos. Meaningful Use data standards in particular have already simplified the task of identifying clinical phenotyping patterns in electronic health records.
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.