Publications by authors named "Ylermi Cabrera-Leon"
Article Synopsis
- The rising population of older adults is leading to a higher incidence of Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI), highlighting the need for early diagnosis.
- An intelligent computing system utilizing a hybrid neural architecture called MyGNG was developed to classify patients into MCI, AD, and cognitively normal categories, based on data from the Alzheimer’s disease neuroimaging initiative.
- The results showed MyGNG's effectiveness, with high sensitivity and area under the curve scores, outperforming traditional machine learning models and suggesting its potential for improving early AD diagnosis.
Background: The growing number of older adults in recent decades has led to more prevalent geriatric diseases, such as strokes and dementia. Therefore, Alzheimer's disease (AD), as the most common type of dementia, has become more frequent too.
Background: Objective: The goals of this work are to present state-of-the-art studies focused on the automatic diagnosis and prognosis of AD and its early stages, mainly mild cognitive impairment, and predicting how the research on this topic may change in the future.
Clinical procedure for mild cognitive impairment (MCI) is mainly based on clinical records and short cognitive tests. However, low suspicion and difficulties in understanding test cut-offs make diagnostic accuracy being low, particularly in primary care. Artificial neural networks (ANNs) are suitable to design computed aided diagnostic systems because of their features of generating relationships between variables and their learning capability.
View Article and Find Full Text PDF