<?xml version='1.0' encoding='UTF-8'?><xml><records><record><source-app name="HighWire" version="7.x">Drupal-HighWire</source-app><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vinall, Maria</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Heraclides, Alexandros</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New and Standard Methods for the Prediction of Type 2 Diabetes Mellitus</style></title><secondary-title><style face="normal" font="default" size="100%">MD Conference Express</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010-11-01 00:00:00</style></date></pub-dates></dates><pages><style  face="normal" font="default" size="100%">16-17</style></pages><abstract><style  face="normal" font="default" size="100%">There is strong evidence that type 2 diabetes mellitus can be prevented by lifestyle modification in high-risk individuals. Efficient identification of at-risk individuals using prediction models is an important component of diabetes treatment, since it can allow for early intervention and permit resources to be focused on those with higher risk.</style></abstract><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">10</style></volume></record></records></xml>