ReviewFrontiers in human neuroscience2023
The current state of artificial intelligence-augmented digitized neurocognitive screening test.
Review in Frontiers in human neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Cognitive Outcomes in Randomized Controlled Trials of Coronary Artery Bypass Graft Surgery From 2005 to 2025: A Systematic Review.Journal of the American Heart Association · 2026Pooled it
- Artificial Intelligence and Digital Biomarkers for Early Detection and Monitoring of Neurological Disorders: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- The Potential of Automated Assessment of Cognitive Function Using Non-Neuroimaging Data: A Systematic Review.Journal of clinical medicine · 2024Review
- Text Dialogue Analysis for Primary Screening of Mild Cognitive Impairment: Development and Validation Study.Journal of medical Internet research · 2023Article
- Cognitive decline assessment in speakers of understudied languages.Alzheimer's & dementia (New York, N. Y.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cognitive screening test is a brief cognitive examination that could be easily performed in a clinical setting. However, one of the main drawbacks of this test was that only a paper-based version was available, which restricts the test to be manually administered and graded by medical personnel at the health centers. The main solution to these problems was to develop a potential remote assessment for screening individuals with cognitive impairment. Currently, multiple studies have been adopting artificial intelligence (AI) technology into these tests, evolving the conventional paper-based neurocognitive test into a digitized AI-assisted neurocognitive test. These studies provided credible evidence of the potential of AI-augmented cognitive screening tests to be better and provided the framework for future studies to further improve the implementation of AI technology in the cognitive screening test. The objective of this review article is to discuss different types of AI used in digitized cognitive screening tests and their advantages and disadvantages.
Indexed as
Identifiers
What OpenQuestion holds
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.