Literature DB >> 22647689

Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project.

Philip R O Payne1, Rebecca D Jackson, Thomas M Best, Tara B Borlawsky, Albert M Lai, Stephen James, Metin N Gurcan.   

Abstract

The conduct of clinical and translational research regularly involves the use of a variety of heterogeneous and large-scale data resources. Scalable methods for the integrative analysis of such resources, particularly when attempting to leverage computable domain knowledge in order to generate actionable hypotheses in a high-throughput manner, remain an open area of research. In this report, we describe both a generalizable design pattern for such integrative knowledge-anchored hypothesis discovery operations and our experience in applying that design pattern in the experimental context of a set of driving research questions related to the publicly available Osteoarthritis Initiative data repository. We believe that this 'test bed' project and the lessons learned during its execution are both generalizable and representative of common clinical and translational research paradigms.

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Mesh:

Year:  2012        PMID: 22647689      PMCID: PMC3534452          DOI: 10.1136/amiajnl-2011-000736

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  18 in total

Review 1.  The osteoarthritis initiative: an overview.

Authors:  Faiza Fawaz-Estrup
Journal:  Med Health R I       Date:  2004-06

2.  Reengineering clinical research with informatics.

Authors:  Thomas K Chung; Rita Kukafka; Stephen B Johnson
Journal:  J Investig Med       Date:  2006-09       Impact factor: 2.895

Review 3.  Clinical research in OA--the NIH Osteoarthritis Initiative.

Authors:  G Lester
Journal:  J Musculoskelet Neuronal Interact       Date:  2008 Oct-Dec       Impact factor: 2.041

Review 4.  Translational informatics: enabling high-throughput research paradigms.

Authors:  Philip R O Payne; Peter J Embi; Chandan K Sen
Journal:  Physiol Genomics       Date:  2009-09-08       Impact factor: 3.107

5.  Medicine. The ultimate model organism.

Authors:  Atul J Butte
Journal:  Science       Date:  2008-04-18       Impact factor: 47.728

6.  Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research.

Authors:  Sufyan Y Ababneh; Jeff W Prescott; Metin N Gurcan
Journal:  Med Image Anal       Date:  2011-02-24       Impact factor: 8.545

7.  An automated method to segment the femur for osteoarthritis research.

Authors:  Jeffrey W Prescott; Michael Pennell; Thomas M Best; Mark S Swanson; Furqan Haq; Rebecca Jackson; Metin N Gurcan
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

8.  Multi-dimensional discovery of biomarker and phenotype complexes.

Authors:  Philip R O Payne; Kun Huang; Kristin Keen-Circle; Abhisek Kundu; Jie Zhang; Tara B Borlawsky
Journal:  BMC Bioinformatics       Date:  2010-10-28       Impact factor: 3.169

9.  Semi-automated segmentation to assess the lateral meniscus in normal and osteoarthritic knees.

Authors:  M S Swanson; J W Prescott; T M Best; K Powell; R D Jackson; F Haq; M N Gurcan
Journal:  Osteoarthritis Cartilage       Date:  2009-11-05       Impact factor: 6.576

10.  Anatomically anchored template-based level set segmentation: application to quadriceps muscles in MR images from the Osteoarthritis Initiative.

Authors:  Jeffrey W Prescott; Thomas M Best; Mark S Swanson; Furqan Haq; Rebecca D Jackson; Metin N Gurcan
Journal:  J Digit Imaging       Date:  2010-01-05       Impact factor: 4.056

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