شناسایی مراحل اختلال شناختی
Abstract
I. Introduction
II. Methods
III. Results
IV. Conclusion
app1. Appendix
Authors
Figures
References
Abstract
Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and dementia associated with Alzheimer’s disease (AD). Early diagnosis of MCI and AD through artificial intelligence has captured considerable scholarly interest; researchers hope to develop therapies capable of slowing or halting these processes. We developed a state-of-the-art deep learning algorithm based on an optimized convolutional neural network (CNN) topology called MCADNNet that simultaneously recognizes MCI, AD, and normally aging brains in adults over the age of 75 years, using structural and functional magnetic resonance imaging (fMRI) data. Following highly detailed preprocessing, fourdimensional (4D) fMRI and 3D MRI were decomposed to create 2D images using a lossless transformation, which enables maximum preservation of data details. The samples were shuffled and subject-level training and testing datasets were completely independent. The optimized MCADNNet was trained and extracted invariant and hierarchical features through convolutional layers followed by multi-classification in the last layer using a softmax layer. A decision-making algorithm was also designed to stabilize the outcome of the trained models. To measure the performance of classification, the accuracy rates for various pipelines were calculated before and after applying the decision-making algorithm. Accuracy rates of 99.77% ± ۰٫۳۶% and 97.5% ± ۱٫۱۶% were achieved for MRI and fMRI pipelines, respectively, after applying the decisionmaking algorithm. In conclusion, a cutting-edge and optimized topology called MCADNNet was designed and preceded a preprocessing pipeline; this was followed by a decision-making step that yielded the highest performance achieved for simultaneous classification of the three cohorts examined.
Introduction
Cognitive impairment is a general term referring to impairments in cognition among the domains of memory, learning, concentration and decision-making. Cognitive impairment ranges from mild to severe and the symptoms can worsen over time and ultimately prevent a patient from performing daily tasks. Mild Cognitive impairment (MCI) was first utilized by Reisberg et al. [1] and is currently defined as a decline in cognitive ability that is detectable however lacking in terms of the severity to alter one’s functioning of daily living. The National Institute on Aging Alzheimer’s Association (NIA-AA) has provided criteria to diagnose dementia and MCI when there occurs a significant cognitive deterioration from an individual’s previous level [2], [3]. Additionally, research demonstrates that elderly adults with a diagnosis of MCI have a higher risk of developing dementia and age-related cognitive decline [4]. Petersen et al.’s research demonstrates that although there is still a scoring threshold in determining MCI, the memory decline of individuals with MCI is approximately1.5 standard deviations below normative data of same age and educationally matched peers [5], [6]. Gallagher et al. indicate depression and anxiety have been reported in almost 50% of individuals with MCI, and a link between depression and anxiety with cognitive decline has been found [7]–[9].