Literature DB >> 12091655

Automatic structuring of radiology reports: harbinger of a second information revolution in radiology.

Curtis P Langlotz.   

Abstract

Mesh:

Year:  2002        PMID: 12091655     DOI: 10.1148/radiol.2241020415

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


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  17 in total

1.  Critical finding capture in the impression section of radiology reports.

Authors:  Esteban F Gershanik; Ronilda Lacson; Ramin Khorasani
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  Development of automated detection of radiology reports citing adrenal findings.

Authors:  Jason J Zopf; Jessica M Langer; William W Boonn; Woojin Kim; Hanna M Zafar
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

3.  Adequacy of paediatric renal tract ultrasound requests and reports in a general radiology department.

Authors:  N Govender; S Andronikou; M D M Goodier
Journal:  Pediatr Radiol       Date:  2011-10-14

4.  Structured reporting using a shared indexed multilingual radiology lexicon.

Authors:  Roberto Stramare; Giuliano Scattolin; Valeria Beltrame; Marco Gerardi; Marco Sommavilla; Cristina Gatto; Paolo Mosca; Leopoldo Rubaltelli; Carlo Riccardo Rossi; Claudio Saccavini
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-10-19       Impact factor: 2.924

Review 5.  Customization of medical report data.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2010-08       Impact factor: 4.056

6.  Conceptual approach for the design of radiology reporting interfaces: the talking template.

Authors:  Chris L Sistrom
Journal:  J Digit Imaging       Date:  2005-09       Impact factor: 4.056

7.  Benefits of the DICOM structured report.

Authors:  Rita Noumeir
Journal:  J Digit Imaging       Date:  2006-12       Impact factor: 4.056

8.  RadiO: a prototype application ontology for radiology reporting tasks.

Authors:  Dirk Marwede; Matthew Fielding; Thomas Kahn
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 9.  Optimizing technology development and adoption in medical imaging using the principles of innovation diffusion, part II: practical applications.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

10.  Improving CT prediction of treatment response in patients with metastatic colorectal carcinoma using statistical learning theory.

Authors:  Walker H Land; Dan Margolis; Ronald Gottlieb; Elizabeth A Krupinski; Jack Y Yang
Journal:  BMC Genomics       Date:  2010-12-01       Impact factor: 3.969

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