Implementing single biomarker formula to predict Alzheimer's disease

Alzheimer's disease (AD) is considered to be a fatal neurodegenerative disease affecting many people over the age of 65. As life expectancies increase around the world, the incidence of AD also grows with it. Current research reports no effective treatment or definitive antemortem diagnostic test for AD. In recent years, a number of biomarkers have been identified for early and accurate diagnosis of the disease but most biomarker diagnostic tests are expensive and involve invasive procedures, resulting in very few AD patients having gone through more than one biomarker test. In this study, a mathematical formula based on single biomarker data has been developed to improve the accuracy of single biomarker prediction of susceptibility to AD. Biomarker datasets used in this work were wholly obtained from other published works.