ArticleStudies in health technology and informatics2022
Prediction of Incident Dementia Using Patient Temporal Health Status.
Article in Studies in health technology and informatics, 2022. 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
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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.
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.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical prediction models using artificial intelligence approaches in dementia.Aging clinical and experimental research · 2025Pooled it
- Predictive factors for dementia among older adults in South Korea: an interpretable machine learning analysis.Alzheimer's research & therapy · 2025Article
- Characterizing the progression from mild cognitive impairment to dementia: a network analysis of longitudinal clinical visits.BMC medical informatics and decision making · 2024Article
- Mild Cognitive Impairment: Data-Driven Prediction, Risk Factors, and Workup.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia.Wiley interdisciplinary reviews. Data mining and knowledge discoveryReview
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Dementia is one of the most prevalent health problems in the aging population. Despite the significant number of people affected, dementia diagnoses are often significantly delayed, missing opportunities to maximize life quality. Early identification of older adults at high risk for dementia may help to maximize current quality of life and to improve planning for future health needs in dementia patients. However, most existing risk prediction models predominantly use static variables, not considering temporal patterns of health status. This study used an attention-based time-aware model to predict incident dementia that incorporated longitudinal temporal health conditions. The predictive performance of the time-aware model was compared with three traditional models using static variables and demonstrated higher predictive power.
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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.