Short-term Prediction of MCI to AD conversion based on Longitudinal MRI analysis and neuropsychological tests

Abstract

Nowadays, 35 million people worldwide su↵er from some form of dementia. Given the increase in life expectancy it is estimated that in 2035 this number will grow to 115 million. Alzheimer’s disease is the most common cause of dementia and it is of great importance diagnose it at an early stage. This is the main goal of this work, the de- velopment of a new automatic method to predict the mild cognitive im- pairment (MCI) patients who will develop Alzheimer’s disease within one year or, conversely, its impairment will remain stable. This technique will analyze data from both magnetic resonance imaging and neuropsycholog- ical tests by utilizing a t-test for feature selection, maximum-uncertainty linear discriminant analysis (MLDA) for classification and leave-one-out cross validation (LOOCV) for evaluating the performance of the meth- ods, which achieved a classification accuracy of 73.95%, with a sensitivity of 72.14% and a specificity of 73.77%.