Machine Learning and Rule-based Approaches to Assertion Classification

Uzuner, Oezlem
Zhang, Xiaoran
Sibanda, Tawanda
Objectives: The authors study two approaches to assertion classification. One of these approaches, Extended NegEx (ENegEx), extends the rule-based NegEx algorithm to cover alter-association assertions; the other, Statistical Assertion Classifier (StAC), presents a machine learning solution to assertion classification.


Recognizing Obesity and Comorbidities in Sparse Data
Uzuner, Oezlem (Oxford University Press (OUP), 2009-07-01)
In order to survey, facilitate, and evaluate studies of medical language processing on clinical narratives, i2b2 (Informatics for Integrating Biology to the Bedside) organized its second challenge and workshop. This challenge focused on automatically extracting information on obesity and fifteen of its most common comorbidities from patient discharge summaries. For each patient, obesity and any of the comorbidities could be Present, Absent, or Questionable (i.e., possible) in the patient, or Unmentioned in ...
Specializing for predicting obesity and its co-morbidities
Goldstein, Ira; Uzuner, Oezlem (Elsevier BV, 2009-10-01)
We present specializing, a method for combining classifiers for multi-class classification. Specializing trains one specialist classifier per class and utilizes each specialist to distinguish that class from all others in a one-versus-all manner. It then supplements the specialist classifiers with a catch-all classifier that performs multi-class classification across all classes. We refer to the resulting combined classifier as a specializing classifier.
Self-construals and values in different cultural and socioeconomic contexts
İmamoğlu, Emine Olcay; Karakitapoglu-Aygun, Z (Informa UK Limited, 2004-11-01)
In this study the authors investigated (a) how individuational and relational self-orientations, as well as self-directed and other-directed values, are related to one another, and (b) how these self- and value orientations differ across 2 cultural (i.e., 422 Turkish and 441 American university students) and 2 socioeconomic status (SES) groups (i.e., 186 lower SES and 167 upper SES Turkish high school students). Across cross-cultural and SES groups, individuational and relational self-orientations appeared ...
Probabilistic Slope Stability Analyses Using Limit Equilibrium and Finite Element Methods
Akbas, Burak; Huvaj Sarıhan, Nejan (2015-10-16)
This paper compares the results of different probabilistic approaches and emphasizes the necessity of probabilistic analyses in slope stability studies. To do that, Limit Equilibrium Method (LEM) and Finite Element Method (FEM) are utilized and their outputs are compared in terms of probability of failure (PF), reliability index (RI), factor of safety (FS) and the failure surface. Lastly, concept of Random Finite Element Method (RFEM) is studied and effects of spatial correlation distance are investigated.
Performance tests of a novel electroencephalographic data-acquisition system
Usakli, Ali Bulent; Gençer, Nevzat Güneri (2007-02-16)
The aim of the this study is to present some performance tests of a novel 256-channel electroencephalographic data-acquisition system. The common mode rejection ratio of the system was measured as 102 dB for signals in the electroencephalography frequency range and 154 dB for de signals. System electrical noise (referred-to-input) is 1.76 mu V (rms) (0.21 mu V/root Hz for 70-Hz bandwidth). The cross-talk rejection was found to be at 58 dB. The dynamic range of the system was found 108 dB. The performance te...
Citation Formats
O. Uzuner, X. Zhang, and T. Sibanda, “Machine Learning and Rule-based Approaches to Assertion Classification,” JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, pp. 109–115, 2009, Accessed: 00, 2020. [Online]. Available: