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An Artificial Intelligence-Assisted Method for Dementia Detection Using Images from the Clock Drawing Test
- Source :
- Journal of Alzheimer's Disease. 83:581-589
- Publication Year :
- 2021
- Publisher :
- IOS Press, 2021.
-
Abstract
- Background: Widespread dementia detection could increase clinical trial candidates and enable appropriate interventions. Since the Clock Drawing Test (CDT) can be potentially used for diagnosing dementia-related disorders, it can be leveraged to develop a computer-aided screening tool. Objective: To evaluate if a machine learning model that uses images from the CDT can predict mild cognitive impairment or dementia. Methods: Images of an analog clock drawn by 3,263 cognitively intact and 160 impaired subjects were collected during in-person dementia evaluations by the Framingham Heart Study. We processed the CDT images, participant’s age, and education level using a deep learning algorithm to predict dementia status. Results: When only the CDT images were used, the deep learning model predicted dementia status with an area under the receiver operating characteristic curve (AUC) of 81.3% ± 4.3%. A composite logistic regression model using age, level of education, and the predictions from the CDT-only model, yielded an average AUC and average F1 score of 91.9% ±1.1% and 94.6% ±0.4%, respectively. Conclusion: Our modeling framework establishes a proof-of-principle that deep learning can be applied on images derived from the CDT to predict dementia status. When fully validated, this approach can offer a cost-effective and easily deployable mechanism for detecting cognitive impairment.
- Subjects :
- Computer science
Machine learning
computer.software_genre
Logistic regression
050105 experimental psychology
03 medical and health sciences
0302 clinical medicine
Framingham Heart Study
medicine
Dementia
0501 psychology and cognitive sciences
Cognitive impairment
Receiver operating characteristic
business.industry
General Neuroscience
Deep learning
05 social sciences
General Medicine
medicine.disease
Psychiatry and Mental health
Clinical Psychology
Artificial intelligence
Geriatrics and Gerontology
business
F1 score
computer
Clock drawing test
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 18758908 and 13872877
- Volume :
- 83
- Database :
- OpenAIRE
- Journal :
- Journal of Alzheimer's Disease
- Accession number :
- edsair.doi...........d28afde6e3b2d8765a633e7bec3eff90
- Full Text :
- https://doi.org/10.3233/jad-210299