ArticleAging2021
Screening of Alzheimer's disease by facial complexion using artificial intelligence.
Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.
- Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis.Frontiers in aging neuroscience · 2025Pooled it
- AI-Based Measurement Tools for Intrinsic Capacity in Older Adults: Scoping Review.Journal of medical Internet research · 2026Article
- Facial phenotypes in Alzheimer's disease: from neurobiology to artificial intelligence.Alzheimer's research & therapy · 2026Review
- Facial Expressions as a Nexus for Health Assessment.Bioengineering (Basel, Switzerland) · 2026Review
- A Hybrid Explainable AI Framework (HXAI) for Accurate and Interpretable Diagnosis of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2025Article
- AI-Based Facial Emotion Analysis for Early and Differential Diagnosis of Dementia.Bioengineering (Basel, Switzerland) · 2025Article
- Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2025Article
- A Feature-Augmented Explainable Artificial Intelligence Model for Diagnosing Alzheimer's Disease from Multimodal Clinical and Neuroimaging Data.Diagnostics (Basel, Switzerland) · 2025Article
- A Meta-Learning-Based Ensemble Model for Explainable Alzheimer's Disease Diagnosis.Diagnostics (Basel, Switzerland) · 2025Article
- Alzheimer's disease and other memory disorders in the age of AI: reflection and perspectives on the 120th anniversary of the birth of Dr. John von Neumann.GeroScience · 2025Review
- Noncontact evaluation of autonomic nervous system activity during exercise by using video analysis.Frontiers in digital health · 2025Article
- Artificial intelligence and omics-based autoantibody profiling in dementia.Frontiers in immunology · 2025Article
- Facial aging, cognitive impairment, and dementia risk.Alzheimer's research & therapy · 2024Article
- Digital detection of Alzheimer's disease using smiles and conversations with a chatbot.Scientific reports · 2024Article
- Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module.Expert systems with applications · 2024Article
- Mild cognitive impairment prediction based on multi-stream convolutional neural networks.BMC bioinformatics · 2024Article
- MC-ViViT: Multi-branch Classifier-ViViT to Detect Mild Cognitive Impairment in Older Adults Using Facial Videos.Expert systems with applications · 2024Article
- Investigation of a model for evaluating cognitive decline from facial photographs using AI.Geriatrics & gerontology international · 2024Article
- Applications of artificial intelligence in dementia.Geriatrics & gerontology international · 2024Review
- 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
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive, and inexpensive method of screening for dementia is yet to be discovered. This study aimed to examine whether artificial intelligence (AI) could distinguish between the faces of people with cognitive impairment and those without dementia.121 patients with cognitive impairment and 117 cognitively sound participants were recruited for the study. 5 deep learning models with 2 optimizers were tested. The binary differentiation of dementia / non-dementia facial image was expressed as a "Face AI score". Xception with Adam was the model that showed the best performance. Overall sensitivity, specificity, and accuracy by the Xception AI system and AUC of the ROC curve were 87.31%, 94.57%, 92.56%, and 0.9717, respectively. Close and significant correlations were found between Face AI score and MMSE (
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.