Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches.
dc.contributor.author | Solti, Imre | |
dc.contributor.author | Cooke, Colin | |
dc.contributor.author | Xia, Fei | |
dc.contributor.author | Wurfel, Mark | |
dc.date.accessioned | 2011-08-17T02:35:46Z | |
dc.date.available | 2011-08-17T02:35:46Z | |
dc.date.issued | 2009-11 | |
dc.identifier.citation | Proceedings (IEEE Int Conf Bioinformatics Biomed). 2009 Nov;2009:314-319. <http://hdl.handle.net/2027.42/85786> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85786 | |
dc.description.abstract | This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to recognize ALI and lead to reductions in mortality. For our study, 96 and 857 chest x-ray reports in two corpora were labeled by domain experts for ALI. We developed a keyword and a Maximum Entropy-based classification system. Word unigram and character n-grams provided the features for the machine learning system. The Maximum Entropy algorithm with character 6-gram achieved the highest performance (Recall=0.91, Precision=0.90 and F-measure=0.91) on the 857-report corpus. This study has shown that for the classification of ALI chest x-ray reports, the machine learning approach is superior to the keyword based system and achieves comparable results to highest performing physician annotators. | en_US |
dc.language.iso | en_US | en_US |
dc.title | Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches. | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Internal Medicine and Specialities | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Pulmonary and Critical Care Medicine, Division of | en_US |
dc.contributor.affiliationum | Internal Medicine, Department of | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85786/1/Solti - Classification of CXR in ALI.pdf | |
dc.identifier.source | Proceedings (IEEE Int Conf Bioinformatics Biomed) | en_US |
dc.owningcollname | Pulmonary & Critical Care Medicine, Division of |
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