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At least 919 records · Page 51Linked to original sources
PubMed2005

Essay: the political logic of regulatory error.

Regulatory error is an issue that has come to the fore following the withdrawal of rofecoxib (Vioxx; Merck) a year ago. Here, we provide a theoretical discussion of the factors that could influence regulatory error, drawing on the Vioxx episode in particular as a possible example of error, and consider the implications for future regulatory policy.

Drug Approval↗
PubMed2000

[Automated detection of spleen volume by spiral CT scans using neural networks and "fuzzy logic"].

PURPOSE: To assess spleen segmentation and volumentry in spiral CT scans with and without pathological changes of splenic tissue. METHODS: The image analysis software HYBRIKON is based on region growing, self-organized neural nets, and fuzzy-anatomic rules. The neural nets were trained with spiral CT data from 10 patients, not used in the following evaluation on spiral CT scans from 19 patients. An experienced radiologist verified the results. The true positive and false positive areas were compared in terms to the areas marked by the radiologist. The results were compared with a standard thresholding method. RESULTS: The neural nets achieved a higher accuracy than the thresholding method. Correlation coefficient of the fuzzy-neural nets: 0.99 (thresholding: 0.63). Mean true positive rate: 90% (thresholding: 75%), mean false positive rate: 5% (thresholding > 100%). Pitfalls were caused by accessory spleens, extreme changes in the morphology (tumors, metastases, cysts), and parasplenic masses. CONCLUSIONS: Self-organizing neural nets combined with fuzzy rules are ready for use in the automatic detection and volumetry of the spleen in spiral CT scans.

Adult↗