Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Bayesian reasoning in an abductive mechanism for argument generation and analysis
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Building natural language generation systems
Building natural language generation systems
A Causal Probabilistic Network for Optimal Treatment of Bacterial Infections
IEEE Transactions on Knowledge and Data Engineering
Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
The reliability of a dialogue structure coding scheme
Computational Linguistics
Recognizing subjectivity: a case study in manual tagging
Natural Language Engineering
International Journal of Intelligent Systems - Computational Models of Natural Argumentation
Query expansion in information retrieval systems using a Bayesian network-based thesaurus
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Editorial: Bayesian networks in biomedicine and health-care
Artificial Intelligence in Medicine
Using literature and data to learn Bayesian networks as clinical models of ovarian tumors
Artificial Intelligence in Medicine
Journal of Biomedical Informatics
Generation of biomedical arguments for lay readers
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
Causal argumentation schemes to support sense-making in clinical genetics and law
Proceedings of the 13th International Conference on Artificial Intelligence and Law
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We developed a Bayesian network coding scheme for annotating biomedical content in layperson-oriented clinical genetics documents. The coding scheme supports the representation of probabilistic and causal relationships among concepts in this domain, at a high enough level of abstraction to capture commonalities among genetic processes and their relationship to health. We are using the coding scheme to annotate a corpus of genetic counseling patient letters as part of the requirements analysis and knowledge acquisition phase of a natural language generation project. This paper describes the coding scheme and presents an evaluation of intercoder reliability for its tag set. In addition to giving examples of use of the coding scheme for analysis of discourse and linguistic features in this genre, we suggest other uses for it in analysis of layperson-oriented text and dialogue in medical communication.