GaNEn: a new gating neural ensemble for automatic assessment of the severity level of dementia using neuropsychological tests

Abstract

Dementia is one of the associated diseases to aging most prevalents. An important issue about this neuropathology, as of yet unsolved, is the absence of therapeutic tools that manage or stop its progression and symptoms in a constant and supported way. In the present study, we propose a new computational intelligent tool to diagnose the Severity Level of Dementia (SLD) using gating neural network and neural ensemble approaches. We present a gating neural ensemble (GaNEn). This system is a new formulation of a neural network ensemble, where the gating neural network takes part in the combination strategy of ensemble system, and the main expert module in its construction is a HUMANN-S (Supervised HUMANN (Hybrid Unsupervised Modular Artificial Neural Network)) architecture. GaNEn is characterized by an incremental capacity concerning missing data management and their influence in the final diagnosis. It improves previous computational solutions and obtains higher accuracy diagnosis. The GaNEn system is a significant achievement in the medical diagnosis of neurological disorders because it could aid in the design of pharmaco-therapeutic strategies to contain dementia. It is also capable of supplying the best neuropsychological scales for dementia severity grades. We have explored its ability using a battery of neuropsychological tests from people with Alzheimer type dementia (AD), Vascular type dementia (VD) and other dementia type (OD) like Trauma, Subcortical, Parkinson and Infectious, from the Alzheimer's Association of Gran Canaria.