Rule based inference engine to forecast the prevalence of congenital malformations in live births

Congenital malformations (CM) are abnormalities of structures arising during the prenatal development and hampering body functions later in life. Causes of CM can be genetic, environmental or any kind of drug exposure during the pregnancy. CM is one of the most important causes of infant mortality in the developing countries. In Pakistan 6-9% of the perinatal deaths are attributed to CM, but a comprehensive nation-wide data on the prevalence, nature and dynamics of CM are largely missing. Hence, the aim of present study is to forecast the prevalence of CM in the multiethnic and multilinguistic population of Rawalpindi/Islamabad through an inference engine. Inference engine helps in formulating new conclusions about the data that is provided to the inference engine and stored in the knowledge base of the inference engine. This pilot engine presents a comprehensive overview of neonatal and maternal parameters and highlights the potential risk factors associated with CM by formulating new conclusions. Additionally, this inference engine would be helpful to establish the dynamics of CM in our society. It is anticipated that such project conducted on a country-wide sample could be highly beneficial in guiding our national health policy, resource allocation and management of CM.