ArticleFrontiers in digital health2021
DCTclock: Clinically-Interpretable and Automated Artificial Intelligence Analysis of Drawing Behavior for Capturing Cognition.
Article in Frontiers in digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
36 citing papers in PubMed, 51 citations in OpenAlex.
- AI-Based Measurement Tools for Intrinsic Capacity in Older Adults: Scoping Review.Journal of medical Internet research · 2026Article
- Neuropsychological Assessment Using Portable Automated Rapid Testing in Cognitively Healthy Older Adults: Test-Retest Reliability Study.JMIR formative research · 2026Article
- Validation of an artificial intelligence-based drawing platform against the Clock Drawing Test for cognitive screening: a comparative study between Alzheimer's disease and healthy controls.Family practice · 2026Article
- Computer Vision Scoring of Figure Copy and Recall.medRxiv : the preprint server for health sciences · 2026Article
- Diagnostic accuracy of digital clock drawing test for Alzheimer disease and mild cognitive impairment.NPJ digital medicine · 2026Article
- Predicting cognitive impairment using novel functional features of spatial proximity and circularity in the digital clock drawing test.medRxiv : the preprint server for health sciences · 2026Article
- Streamlining Eligibility Assessment for Alzheimer's Disease-Modifying Therapies: Prediction of MMSE Scores Using the Digital Clock and Recall.medRxiv : the preprint server for health sciences · 2026Article
- Higher Amyloid and Tau Burden Is Associated With Faster Decline on a Digital Cognitive Test.Annals of clinical and translational neurology · 2026Article
- Semi-Supervised Clustering for Identification of MCI and Dementia Cohorts with a Brief Digital Cognitive Assessment.Research square · 2026Article
- Digital clock assessment in South Asian setting: pilot study.NPJ dementia · 2026Article
- Streamlining eligibility assessment for Alzheimer's disease-modifying therapies: Prediction of MMSE scores using the digital clock and recall.Frontiers in digital health · 2026Article
- Concurrent detection of cognitive impairment and amyloid positivity with a multimodal machine learning-enabled digital cognitive assessment.Alzheimer's research & therapy · 2025Article
- Performance of Older Adults on the Digital Clock and Recall Test Compared to the Montreal Cognitive Assessment in Primary Care Settings.Journal of general internal medicine · 2025Article
- Digital Clock Assessment in South Asian Setting: Pilot study.Research square · 2025Article
- Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology.Biomimetics (Basel, Switzerland) · 2025Review
- Article
- Feasibility and Acceptability of Implementing a Digital Cognitive Assessment for Alzheimer Disease and Related Dementias in Primary Care.Annals of family medicine · 2025Article
- PENSIEVE-AI a brief cognitive test to detect cognitive impairment across diverse literacy.Nature communications · 2025Article
- Clinical validation of a novel hand dexterity measurement device.PLOS digital health · 2025Article
- Digital speech hearing screening using a quick novel mobile hearing impairment assessment: an observational correlation study.Scientific reports · 2024Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developing tools for efficiently measuring cognitive change specifically and brain health generally-whether for clinical use or as endpoints in clinical trials-is a major challenge, particularly for conditions such as Alzheimer's disease. Technology such as connected devices and advances in artificial intelligence offer the possibility of creating and deploying clinical-grade tools with high sensitivity, rapidly, cheaply, and non-intrusively. Starting from a widely-used paper and pencil cognitive status test-The Clock Drawing Test-we combined a digital input device to capture time-stamped drawing coordinates with a machine learning analysis of drawing behavior to create DCTclock™, an automated analysis of nuances in cognitive performance beyond successful task completion. Development and validation was conducted on a dataset of 1,833 presumed cognitively unimpaired and clinically diagnosed cognitively impaired individuals with varied neurological conditions. We benchmarked DCTclock against existing clock scoring systems and the Mini-Mental Status Examination, a widely-used but lengthier cognitive test, and showed that DCTclock offered a significant improvement in the detection of early cognitive impairment and the ability to characterize individuals along the Alzheimer's disease trajectory. This offers an example of a robust framework for creating digital biomarkers that can be used clinically and in research for assessing neurological function.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.