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Machine Learning Behavioral Recognition to Support Neuropsychological Diagnosis of Cognitive Decline

Published: 05 March 2018 Publication History

Abstract

With nearly 93,500 deaths were attributed to Alzheimer's Disease in 2014 and numbers projected to climb, medical experts have recently placed increasing emphasis in the early detection of Alzheimer's disease and other types of dementia. An open challenge in early detection is developing standardized testing that helps clinicians detect subtle signs of Mild Cognitive Impairment that occur prior to the development of said dementias. In this regard we present our preliminary work on leveraging machine-learning behavioral classification to detect subtle behavioral abnormalities. Our framework consists of detecting behavioral abnormalities through the computerization of an existing paper-based clinical neuropsychological tests as well as the development of novel tests that could only be realized with modern touch tablet technology.

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  • (2021)Detecting Children’s Fine Motor Skill Development using Machine LearningInternational Journal of Artificial Intelligence in Education10.1007/s40593-021-00279-732:4(991-1024)Online publication date: 19-Oct-2021

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cover image ACM Conferences
IUI '18: Proceedings of the 23rd International Conference on Intelligent User Interfaces
March 2018
698 pages
ISBN:9781450349451
DOI:10.1145/3172944
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 March 2018

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Author Tags

  1. Alzheimer's disease
  2. clinical neuropsychology
  3. human-computer interaction
  4. machine learning classification
  5. mild cognitive impairment

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IUI '18 Paper Acceptance Rate 43 of 299 submissions, 14%;
Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

View all
  • (2021)Detecting Children’s Fine Motor Skill Development using Machine LearningInternational Journal of Artificial Intelligence in Education10.1007/s40593-021-00279-732:4(991-1024)Online publication date: 19-Oct-2021

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