This paper is in the following e-collection/theme issue:

New Methods (944) Dementia and Cognitive Decline (481) Diagnostic Tools in Mental Health (242) Research Instruments, Questionnaires, and Tools (576) Cognitive Training for the Elderly (95) Methods and New Tools in Mental Health Research (454)

Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27407, first published .
Association Between the Digital Clock Drawing Test and Neuropsychological Test Performance: Large Community-Based Prospective Cohort (Framingham Heart Study)

Association Between the Digital Clock Drawing Test and Neuropsychological Test Performance: Large Community-Based Prospective Cohort (Framingham Heart Study)

Association Between the Digital Clock Drawing Test and Neuropsychological Test Performance: Large Community-Based Prospective Cohort (Framingham Heart Study)

Authors of this article:

Jing Yuan1, 2 Author Orcid Image ;   David J Libon3 Author Orcid Image ;   Cody Karjadi4 Author Orcid Image ;   Alvin F A Ang2, 4, 5 Author Orcid Image ;   Sherral Devine2, 4 Author Orcid Image ;   Sanford H Auerbach4, 6 Author Orcid Image ;   Rhoda Au2, 4, 5, 6, 7 Author Orcid Image ;   Honghuang Lin4, 8 Author Orcid Image
Article Authors Cited by (19) Tweetations (4) Metrics

Journals

  1. Park I, Lee U. Automatic, Qualitative Scoring of the Clock Drawing Test (CDT) Based on U-Net, CNN and Mobile Sensor Data. Sensors 2021;21(15):5239 View
  2. Zlatar Z, Campbell L, Tang B, Gabin S, Heaton A, Higgins M, Swendsen J, Moore D, Moore R. Daily Level Association of Physical Activity and Performance on Ecological Momentary Cognitive Tests in Free-living Environments: A Mobile Health Observational Study. JMIR mHealth and uHealth 2022;10(1):e33747 View
  3. Sato K, Niimi Y, Mano T, Iwata A, Iwatsubo T. Automated Evaluation of Conventional Clock-Drawing Test Using Deep Neural Network: Potential as a Mass Screening Tool to Detect Individuals With Cognitive Decline. Frontiers in Neurology 2022;13 View
  4. Yuan J, Au R, Karjadi C, Ang T, Devine S, Auerbach S, DeCarli C, Libon D, Mez J, Lin H. Associations Between the Digital Clock Drawing Test and Brain Volume: Large Community-Based Prospective Cohort (Framingham Heart Study). Journal of Medical Internet Research 2022;24(4):e34513 View
  5. Kobayashi M, Yamada Y, Shinkawa K, Nemoto M, Nemoto K, Arai T, Price C. Automated Early Detection of Alzheimer’s Disease by Capturing Impairments in Multiple Cognitive Domains with Multiple Drawing Tasks. Journal of Alzheimer's Disease 2022;88(3):1075 View
  6. Ding H, Mandapati A, Karjadi C, Ang T, Lu S, Miao X, Glass J, Au R, Lin H. Association Between Acoustic Features and Neuropsychological Test Performance in the Framingham Heart Study: Observational Study. Journal of Medical Internet Research 2022;24(12):e42886 View
  7. Kehl-Floberg K, Marks T, Edwards D, Giles G. Conventional clock drawing tests have low to moderate reliability and validity for detecting subtle cognitive impairments in community-dwelling older adults. Frontiers in Aging Neuroscience 2023;15 View
  8. Potestio C, Dibato J, Bolkus K, Awad A, Thayasivam U, Patel A, Bright A, Mitrev L. Post-Operative Cognitive Dysfunction in Elderly Patients Receiving Propofol Sedation for Gastrointestinal Endoscopies: An Observational Study Utilizing Processed Electroencephalography. Cureus 2023 View
  9. Sejunaite K, Gaucher F, Lanza C, Riepe M, Abbate C. Clock Drawing Test: Types of Errors and Accuracy in Early Cognitive Screening. Journal of Alzheimer's Disease 2023;95(4):1597 View
  10. Ding H, Hamel A, Karjadi C, Ang T, Lu S, Thomas R, Au R, Lin H. Association between acoustic features and brain volumes: the Framingham Heart Study. Frontiers in Dementia 2023;2 View
  11. Yamauchi S, Kawano N, Shimazaki K, Shinkai H, Kojima M, Shinohara K, Aoki H. Digital clock drawing test reflects visuospatial ability of older drivers. Frontiers in Psychology 2024;15 View
  12. Park J. Non-equivalence of sub-tasks of the Rey-Osterrieth Complex Figure Test with convolutional neural networks to discriminate mild cognitive impairment. BMC Psychiatry 2024;24(1) View
  13. Han D, Kim S, Kim S. Brain activation in response to art-based tasks using diverse materials based on the Expressive Therapy Continuum (ETC). The Arts in Psychotherapy 2024;90:102185 View
  14. Wang J, Huang B, Zhou L, Tang S, Feng H, Chan J, Chau S, Zhang J, Li S, Mok V, Wing Y, Liu Y. Visuospatial dysfunction predicts dementia-first phenoconversion in isolated REM sleep behaviour disorder. Journal of Neurology, Neurosurgery & Psychiatry 2024:jnnp-2024-333865 View
  15. Gomes-Osman J, Borson S, Toro-Serey C, Banks R, Ciesla M, Jannati A, Morrow W, Swenson R, Libon D, Bates D, Showalter J, Tobyne S, Pascual-Leone A. Digital Clock and Recall: a digital, process-driven evolution of the Mini-Cog. Frontiers in Human Neuroscience 2024;18 View

Books/Policy Documents

  1. An N, Hu E, Guo Y, Yang J, Au R, Ding H. HCI International 2022 – Late Breaking Papers: HCI for Health, Well-being, Universal Access and Healthy Aging. View
  2. de Almondes K, Alves G, Alves C. Advances in Neuroscience, Neuropsychiatry, and Neurology. View
  3. Lan M, Xu Z, Yang H, Wang H, Lei N, Lu T, Li J, Gao L. Proceedings of Ninth International Congress on Information and Communication Technology. View