To serve its constituents in the most cost-effective manner, regulatory organizations must use the best possible means to prioritize spending on expensive laboratory testing.
MAFF used Clementine¹s neural networks and rule induction algorithms to find patterns in data that help predict potentially harmful chemicals found in food.
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As a leading U.K. regulatory organization, the Ministry of Agriculture Fisheries and Food helps improve overall food safety. Specifically, it must take an in-depth look at substances added to food and analyze risk from those substances. MAFF accomplishes this is by studying chemicals or food ingredients and whether they are likely to affect the people and animals who consume them. Since much data describing the toxicity of chemicals exists and MAFF must continually investigate thousands of chemicals used as flavorings and preservatives, it had to determine the most efficient means to help its scientists assess toxicity. To begin, MAFF - aided by SPSS and other data mining consultants - merged two large publicly available databases to mine detailed chemical information.
Without Clementine, analyzing this amount of data would have taken months. Using Clementine, it took just weeks.
Once data were ready for mining, MAFF applied Clementine¹s neural networks in combination with rule induction to predict the harmfulness of the chemicals in the database. Without Clementine, analyzing this amount of data would have taken months. Using Clementine, it took only weeks.
Today, toxicologists use the Clementine model to quickly and easily flag a substance as toxic, which they can then further investigate. As a result, MAFF is making more effective use of taxpayers' money, and further contributing to public health and safety.
Prioritizing its resources enables MAFF to concentrate its resources on a few substances, thus reducing the need for animal testing. What¹s more, as analytical methods become a more valuable means to predict toxicity, the positive effects of work done with the Clementine model will touch more than just U.K. consumers, as free trade is allowed in food throughout the European Union.
The complete list of global SPSS success stories can be found here
“Without Clementine,
analyzing this amount
of data would have
taken months. Using
Clementine, it took
only weeks.”
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