01577nas a2200241   4500000000100000000000100001008004100002260001200043653001600055653002500071653001300096653001300109653001300122653002500135653001000160100003100170245009100201856009800292300001000390490000600400520091500406022001401321       2016                            d  c03/201610aData Mining10aKnowledge Management10aAnalysis10aBig Data10aMedicine10aPredictive Modelling10aDrugs1 aRafael San-Miguel Carrasco00aDetection of Adverse Reaction to Drugs in Elderly Patients through Predictive Modeling  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/02/ijimai20163_6_8_pdf_12774.pdf  a52-560 v33 aGeriatrics Medicine constitutes a clinical research field in which data analytics, particularly predictive modeling, can deliver compelling, reliable and long-lasting benefits, as well as non-intuitive clinical insights and net new knowledge. The research work described in this paper leverages predictive modeling to uncover new insights related to adverse reaction to drugs in elderly patients. The differentiation factor that sets this research exercise apart from traditional clinical research is the fact that it was not designed by formulating a particular hypothesis to be validated. Instead, it was data-centric, with data being mined to discover relationships or correlations among variables. Regression techniques were systematically applied to data through multiple iterations and under different configurations. The obtained results after the process was completed are explained and discussed next.  a1989-1660