Jain NL, Knirsch CA, Friedman C, Hripcsak G. Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports. Proc AMIA Annu Fall Symp 1996;542-6. Home/Search Document Not in Database Summary Related Articles Check |
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Automatic Prediction of Trauma Registry Procedure.. - Hersh, Leen, Rehfuss, .. (1998) (1 citation) (Correct)
.... of the earliest efforts, showing that for limited domains using cleansed (i.e. spelling errors correction, heading and other non clinical information removed) data, 80 90 of concepts could be recognized [1] Some have also integrated NLP functions into EMRs for recognition of clinical events [2,3]. Others have attempted to predict diagnosis codes based on words that occur in discharge summaries [4] or exacerbations of asthma based on progress notes [5] The goal of unrestricted NLP, however, has not been met. All of the above systems work in limited domains and, while very valuable to ....
Jain N, Knirsch C, Friedman C, Hripcsak G. Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports. In: Cimino J, ed. Proceedings of the 19th Annual AMIA Fall Symposium. Washington, DC: Hanley-Belfus, 1996:542-546.
Medical Text Representations for Inductive Learning - Adam Wilcox Ph (2000) Self-citation (Hripcsak) (Correct)
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Jain NL, Knirsch CA, Friedman C, Hripcsak G. Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports. Proc AMIA Annu Fall Symp 1996;542-6.
Evaluating Natural Language Processors in the Clinical Domain - Friedman, Hripcsak (1997) (6 citations) Self-citation (Friedman Hripcsak) (Correct)
....for all measures. An analysis as to the possible sources of disagreement among the experts was discussed. One problem with this study is that intra rater agreement was not measured and a break down of the source of problems caused by the automated system was not given. A fourth evaluation study [14] was performed on MedLEE that was designed and carried out by another independent evaluator. This study was a retrospective study to determine if MedLEE could identify patients at risk for having tuberculosis based on their admission chest radiographs. No special training was performed on MedLEE ....
Jain N, Knirsch C, Friedman C, and Hripcsak G. Identification of Suspected Tuberculosis Patients based on Natural Language Processing of Chest Radiograph Reports.Cimino J. Proceedings of the 1996 AMIA Annual Fall Symposium. Philadephia. Belfus & Hanley. 1996;p542-6.
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