2008 - Obesity

Bibliographic References tagged with 2008 - Obesity

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Uzuner Ö. Recognizing Obesity and Comorbidities in Sparse Data.
Journal of the American Medical Informatics Association. 2009;16(4):561–570.
Uzuner Ö. Recognizing Obesity and Comorbidities in Sparse Data.
Journal of the American Medical Informatics Association. 2009;16(4):561–570.
Childs LC, Enelow R, Simonsen L, Heintzelman NH, Kowalski KM, Taylor RJ. Description of a Rule-based System for the i2b2 Challenge in Natural Language Processing for Clinical Data.
Journal of the American Medical Informatics Association. 2009;16(4):571–575.
Childs LC, Enelow R, Simonsen L, Heintzelman NH, Kowalski KM, Taylor RJ. Description of a Rule-based System for the i2b2 Challenge in Natural Language Processing for Clinical Data.
Journal of the American Medical Informatics Association. 2009;16(4):571–575.
Mishra NK, Cummo DM, Arnzen JJ, Bonander J. A Rule-based Approach for Identifying Obesity and Its Comorbidities in Medical Discharge Summaries.
Journal of the American Medical Informatics Association. 2009;16(4):576–579.
Mishra NK, Cummo DM, Arnzen JJ, Bonander J. A Rule-based Approach for Identifying Obesity and Its Comorbidities in Medical Discharge Summaries.
Journal of the American Medical Informatics Association. 2009;16(4):576–579.
Solt I, Tikk D, Gál V, Kardkovács ZT. Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier.
Journal of the American Medical Informatics Association. 2009;16(4):580–584.
Solt I, Tikk D, Gál V, Kardkovács ZT. Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier.
Journal of the American Medical Informatics Association. 2009;16(4):580–584.
Ware H, Mullett CJ, Jagannathan V. Natural Language Processing Framework to Assess Clinical Conditions.
Journal of the American Medical Informatics Association. 2009;16(4):585–589.
Ware H, Mullett CJ, Jagannathan V. Natural Language Processing Framework to Assess Clinical Conditions.
Journal of the American Medical Informatics Association. 2009;16(4):585–589.
Ambert KH, Cohen AM. A System for Classifying Disease Comorbidity Status from Medical Discharge Summaries Using Automated Hotspot and Negated Concept Detection.
Journal of the American Medical Informatics Association. 2009;16(4):590–595.
Ambert KH, Cohen AM. A System for Classifying Disease Comorbidity Status from Medical Discharge Summaries Using Automated Hotspot and Negated Concept Detection.
Journal of the American Medical Informatics Association. 2009;16(4):590–595.
Yang H, Spasic I, Keane JA, Nenadic G. A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries.
Journal of the American Medical Informatics Association. 2009;16(4):596–600.
Yang H, Spasic I, Keane JA, Nenadic G. A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries.
Journal of the American Medical Informatics Association. 2009;16(4):596–600.
Farkas R, Szarvas G, Hegedűs I, Almási A, Vincze V, Ormándi R, Busa-Fekete R. Semi-automated Construction of Decision Rules to Predict Morbidities from Clinical Texts.
Journal of the American Medical Informatics Association. 2009;16(4):601–605.
Farkas R, Szarvas G, Hegedűs I, Almási A, Vincze V, Ormándi R, Busa-Fekete R. Semi-automated Construction of Decision Rules to Predict Morbidities from Clinical Texts.
Journal of the American Medical Informatics Association. 2009;16(4):601–605.