|Title||QA-driven guidelines generation for bacteriotherapy.|
|Publication Type||Journal Article|
|Year of Publication||2009|
|Authors||Pasche, E, Teodoro, D, Gobeill, J, Ruch, P, Lovis, C|
|Journal||AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium|
|Keywords||Anti-Bacterial Agents, Automatic Data Processing, Bacterial Infections, Data Mining, Decision Support Techniques, Humans, Information Storage and Retrieval, Practice Guidelines as Topic, PubMed, Search Engine, Vocabulary, Controlled|
PURPOSE: We propose a question-answering (QA) driven generation approach for automatic acquisition of structured rules that can be used in a knowledge authoring tool for antibiotic prescription guidelines management.
METHODS: The rule generation is seen as a question-answering problem, where the parameters of the questions are known items of the rule (e.g. an infectious disease, caused by a given bacterium) and answers (e.g. some antibiotics) are obtained by a question-answering engine.
RESULTS: When looking for a drug given a pathogen and a disease, top-precision of 0.55 is obtained by the combination of the Boolean engine (PubMed) and the relevance-driven engine (easyIR), which means that for more than half of our evaluation benchmark at least one of the recommended antibiotics was automatically acquired by the rule generation method.
CONCLUSION: These results suggest that such an automatic text mining approach could provide a useful tool for guidelines management, by improving knowledge update and discovery.
|Alternate Journal||AMIA Annu Symp Proc|