Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions

Journal article


Javed, A. R., Saadia, A., Mughal, H., Gadekallu, T.R., Rizwan, M., Maddikunta, P.K.R., Mahmud, M., Liyanage, M and Hussain, A. 2023. Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions. Cognitive Computation. pp. 1-46. https://doi.org/10.1007/s12559-023-10153-4
AuthorsJaved, A. R., Saadia, A., Mughal, H., Gadekallu, T.R., Rizwan, M., Maddikunta, P.K.R., Mahmud, M., Liyanage, M and Hussain, A.
Abstract

The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led many researchers to explore ways to automate the process to make it more objective and to facilitate the needs of the healthcare industry. Artificial Intelligence (AI) and machine learning (ML) have emerged as the most promising approaches to automate the CHA process. In this paper, we explore the background of CHA and delve into the extensive research recently undertaken in this domain to provide a comprehensive survey of the state-of-the-art. In particular, a careful selection of significant works published in the literature is reviewed to elaborate a range of enabling technologies and AI/ML techniques used for CHA, including conventional supervised and unsupervised machine learning, deep learning, reinforcement learning, natural language processing and image processing techniques. Furthermore, we provide an overview of various means of data acquisition and the benchmark datasets. Finally, we discuss open issues and, challenges in using AI and ML for CHA along with some possible solutions. In summary, this paper presents CHA tools, lists various data acquisition methods for CHA, provides technological advancements, presents the usage of AI for CHA, and open issues, challenges in the CHA domain. We hope this first-of-its-kind survey paper will significantly contribute to identifying research gaps in the complex and rapidly evolving interdisciplinary mental health field.

KeywordsHealthcare; Internet of Things; Healthcare services; Remote monitoring; Smart homes; Sustainability; Mental health; Cognitive health; Dementia
Year2023
JournalCognitive Computation
Journal citationpp. 1-46
PublisherSpringer
ISSN1866-9964
Digital Object Identifier (DOI)https://doi.org/10.1007/s12559-023-10153-4
Web address (URL)https://link.springer.com/article/10.1007/s12559-023-10153-4
Accepted author manuscript
File Access Level
Open
Output statusPublished
Publication dates
Online24 Jun 2023
Publication process dates
Accepted01 May 2023
Deposited29 Jun 2023
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https://repository.derby.ac.uk/item/9z390/artificial-intelligence-for-cognitive-health-assessment-state-of-the-art-open-challenges-and-future-directions

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