caTIES: a grid based system for coding and retrieval of surgical pathology reports and tissue specimens in support of translational research.
The authors report on the development of the Cancer Tissue Information Extraction System (caTIES)--an application that supports collaborative tissue banking and text mining by leveraging existing natural language processing methods and algorithms, grid communication and security frameworks, and query visualization methods. The system fills an important need for text-derived clinical data in translational research such as tissue-banking and clinical trials. The design of caTIES addresses three critical issues for informatics support of translational research: (1) federation of research data sources derived from clinical systems; (2) expressive graphical interfaces for concept-based text mining; and (3) regulatory and security model for supporting multi-center collaborative research. Implementation of the system at several Cancer Centers across the country is creating a potential network of caTIES repositories that could provide millions of de-identified clinical reports to users. The system provides an end-to-end application of medical natural language processing to support multi-institutional translational research programs.
Crowley
Rebecca S
RS
Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15232, USA. crowleyrs@upmc.edu
Castine
Melissa
M
Mitchell
Kevin
K
Chavan
Girish
G
McSherry
Tara
T
Feldman
Michael
M
D018070:Biological Specimen Banks; D003196:Computer Graphics; D016494:Computer Security; D057225:Data Mining; D006801:Humans; D033181:Information Dissemination; D007373:Interinstitutional Relations; D015337:Multicenter Studies as Topic; D009323:Natural Language Processing; D009369:Neoplasms / Q000473:pathology* / Q000601:surgery; D057170:Translational Research, Biomedical; D014481:United States; D014584:User-Computer Interface