Discerning tumor status from unstructured MRI reports-completeness of information in existing reports and utility of automated natural language processing

Journal of Digital Imaging

Volumn 23, Issue 2, 2010, Pages 119-132

  Cheng, Lionel T E ^a   Zheng, Jiaping ^a   Savova, Guergana K ^a   Erickson, Bradley J ^a  

^a MAYO CLINIC   (United States)

Author keywords

Natural language processing; Radiology reports; Structured; Tumor status; Unstructured

Indexed keywords

BRAIN TUMORS; CLASSIFICATION ,; CLINICAL DATA; DATA EXTRACTION; DATA RETRIEVAL; DISEASE DETECTION; DISEASE PROGRESSION; ELECTRONIC DATABASE; ELECTRONIC MEDICAL RECORD; GOLD STANDARDS; HUMAN TUMORS; NATURAL LANGUAGE PROCESSING; NEGATIVE PREDICTIVE VALUE; NLP TOOLS; NOVEL APPLICATIONS; POSITIVE PREDICTIVE VALUES; RADIOLOGY REPORTS; RULE BASED; STATUS DETERMINATION; TERTIARY CENTERS; TEXT FORMAT; TUMOR SIZE;

COMPUTATIONAL LINGUISTICS; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; NATURAL LANGUAGE PROCESSING SYSTEMS; RADIATION; RADIOLOGY; RESONANCE; TUMORS;

CLASSIFICATION (OF INFORMATION);

FEMALE; HOSPITAL INFORMATION SYSTEM; HUMAN; INFORMATION PROCESSING; INFORMATION RETRIEVAL; MALE; MEDICAL RECORD; METHODOLOGY; NATURAL LANGUAGE PROCESSING; NEOPLASM; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; REVIEW; SENSITIVITY AND SPECIFICITY; STANDARD; UTILIZATION REVIEW;

AUTOMATIC DATA PROCESSING; FEMALE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MAGNETIC RESONANCE IMAGING; MALE; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; NATURAL LANGUAGE PROCESSING; NEOPLASMS; RADIOLOGY INFORMATION SYSTEMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 77952241648     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/s10278-009-9215-7     Document Type: Article

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