Use of Predictive Modelling in Alzheimer's Detection

Abstract

Alzheimer’s disease is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills, and, eventually, the ability to conduct the simplest tasks [1] .The changes related to Alzheimer’s disease can occur in an individual much before the onset of the disease. Identifying individuals in pre-symptomatic stages is important to slow the progression of the disease and in some cases prevent the occurrence of the symptoms. Therefore, accessibility and availability of right information is vital for early interventions and achieving patient-centered care. The use of predictive modeling facilitates access to such information and more importantly shares information easily with the patient’s healthcare team thus benefiting patient’s outcomes. The aim of this paper is to understand how the use of predictive models can help with Alzheimer’s detection and discuss the challenges with the models.