About this Research Topic

Background

Recent studies have suggested that early intervention is beneficial for patients with dementia. Early detection of cognitive decline is crucial for early intervention and case selection in clinical trials for patients with dementia (especially Alzheimer's disease). Unfortunately, recent studies have reported inconsistent findings in terms of sensitivity of cognitive assessment in detecting the earliest cognitive symptoms of dementia. In addition, the utility of early cognitive assessment in predicting the functional decline of people suspected of early stages of dementia remains unclear. These inconsistent findings concerning the utility of cognitive assessment in the earliest stages of dementia may be attributable to differences in the efficacy of the assessment tools used across the studies. Normal aging may also be associated with changes in cognitive functions. The ability of cognitive assessment methods to differentiate normal aging from pathological aging is another fundamental aspect needed to be considered when aiming at specifically detecting early cognitive symptoms of dementia.

The goals of this Research Topic are: to help solve the current controversies and inefficiency in the detection of early cognitive symptoms of dementia; to highlight new strategies and technological advancements to develop methods assessing early cognitive symptoms and predicting dementia progression; to improve the case selection in clinical trials on early treatments for dementia.

We welcome any types of manuscripts supported by the Journal (including Original Research, Review, Methods, etc.) pertaining to the following themes:
i) the validity of cognitive assessment in evaluating mental processes related to early stages of dementia
ii) the predictive values of cognitive assessment on cognitive decline among individuals suspected to have early stages of dementia
iii) applying non-intrusive engineering and computer tools for cognitive and behavioral assessment of individuals suspected to have early stages of dementia.

This Research Topic is open to contributions from multidisciplinary domains, including but not limited to, the combination of clinical neurology, neuropsychology, neuroscience, neuroimaging, psychometrics, machine learning and artificial intelligence, biosignal processing, and other innovative engineering methods.

Prof. Mohammad Mahoor is a co-author on patent applications for: robotic head (US Patent # 9,810,975), method and system for human tissue analysis (US Patent # 10,839,510), motor task electrophysiological detection (US Patent # 10,588,534), socially assistive robot (US Patent # 11,279,041), therapeutic social robot (2020/0406468). Prof. Mahoor is also the co-founder and co-owner of DreamFace Technologies, LLC. The other Topic Editors declare no competing interests with regard to the Research Topic subject.

Keywords: machine learning, artificial intelligence, Alzheimer's disease, classification, dementia, mild cognitive impairment, neuropsychological assessment, cognitive functions, early detection

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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