Hypertension with aging is a major medical concern even in this ultramodern era of advanced therapies. Preliminary testing is a key element in analyzing the procedures of mild abnormality of blood pressure for a substantial period of time, but presently has a limited value in the prediction of progression to hypertension. Although hypotension, low blood pressure in common parlance, is less common among the ones with abnormal blood pressure, but the adverse effect it has on their health is equivalent to that of hypertension.

Although recent studies have hypothesized that, keeping other factors constant, hemoglobin level is positively associated with blood pressure in a large cohort of healthy individuals, but genetic causes are also prominent in some of individuals. However, there are numerous other factors which determine whether an individual is likely to develop this abnormality.

Data scientists lay out the hypothesis that newer statistical classification methods derived from data mining and machine learning methods are capable of reducing the prediction error manifolds and help cardiologists to conduct a two-tailed preliminary prediction of abnormality of blood pressure in an individual.

Employing statistical techniques, conduct a preliminary prognosis of Hypertension/hypotension, based on the level of hemoglobin and genetic history of the individual.