@article{baceanu_expert_2009,
	title = {The expert explorer: a tool for hospital data visualization and adverse drug event rules validation},
	volume = {148},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {The expert explorer},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_psip_expertexplorer.pdf},
	abstract = {An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Băceanu, Adrian and Atasiei, Ionuţ and Chazard, Emmanuel and Leroy, Nicolas and {PSIP Consortium}},
	year = {2009},
	pmid = {19745238},
	keywords = {Data Mining, Drug Toxicity, Hospital Information Systems, Humans, Internet, Reproducibility of Results, Software Design},
	pages = {85--94},
}

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For that purpose, a software called \"Expert Explorer\" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. 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