Evidence map›Paper›PMID 24039624›Full record

ArticlePersonalized medicine2013

Personalized medicine: challenges and opportunities for translational bioinformatics.

Casey Lynnette Overby, Peter Tarczy-Hornoch

Abstract read
In one paragraph

Article in Personalized medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Patients' Experiences of a Precision Medicine Clinic.Journal of patient experience · 2024
    Article
  3. 3D Bioprinting for Next-Generation Personalized Medicine.International journal of molecular sciences · 2023
    Review
  4. Assessing the net benefit of machine learning models in the presence of resource constraints.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Empowering Personalized Medicine with Big Data and Semantic Web Technology: Promises, Challenges, and Use Cases.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Casey Lynnette OverbyProgram in Personalized & Genomic Medicine and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Peter Tarczy-Hornoch

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
INSTITUTE FOR TRANSLATIONAL HEALTH SCIENCE (UL1): BPCAUL1RR025014 · NCRR · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2007 to 2011
$51.5M
Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
Clinical sequencing in cancer: Clinical ethical and technological studiesU01HG006507 · NHGRI · UNIVERSITY OF WASHINGTON · PI JARVIK, GAIL PAIRITZ · 2012 to 2016
$10.6M
NCATS NIH HHS UL1 TR002319NCRR NIH HHS UL1 RR025014NHGRI NIH HHS T32 HG000035NHGRI NIH HHS U01 HG006507NLM NIH HHS T15 LM007079NLM NIH HHS T15 LM007442
6 · The paper itself

Abstract

Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US President's Council of Advisors on Science and Technology reports illustrate challenges in personalized medicine (in a 2008 report) and in use of health information technology (in a 2010 report). Translational bioinformatics is a field that can help address these challenges and is defined by the American Medical Informatics Association as "the development of storage, analytic and interpretive methods to optimize the transformation of increasing voluminous biomedical data into proactive, predictive, preventative and participatory health." This article discusses barriers to implementing genomics applications and current progress toward overcoming barriers, describes lessons learned from early experiences of institutions engaged in personalized medicine and provides example areas for translational bioinformatics research inquiry.

Indexed as

biobanksclinical decision supportcomputational analyseseducationelectronic health recordsimplementation challengesindividual research resultspersonalized medicinetranslational bioinformaticstranslational research

Identifiers

PMID24039624
PMCPMC3770190

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.