ReviewJAMIA open2021
Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review.
Review in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses 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
51 citing papers in PubMed, 3 syntheses or guidelines pooled it, 119 citations in OpenAlex.
- Applications of Machine Learning for Cognitive Health in Older Individuals With HIV: Rapid Systematic Review.JMIR aging · 2025Pooled it
- Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.JMIR aging · 2024Pooled it
- Pooled it
- Genetic and pathway complexity in Alzheimer's disease: Insights from multi-omic data about the immune response and mitochondrial function.Neural regeneration research · 2026Article
- Genetic Associations with Temporal Modeling of Alzheimer's Disease Progression Supports a Novel Paradigm for Disease Risk.medRxiv : the preprint server for health sciences · 2026Article
- A dynamic risk prediction framework for Alzheimer's disease and related dementias with interpretability.NPJ digital medicine · 2026Article
- Advancing diagnostic biomarkers in Alzheimer's disease: interdisciplinary innovations and technological frontiers.Human cell · 2026Review
- Identifying Alzheimer's Disease Progression Subphenotypes Via a Graph-based Framework Using Electronic Health Records.Journal of healthcare informatics research · 2026Article
- Disease progression modeling of Alzheimer's disease based on variational probability principal component analysis.PloS one · 2026Article
- Construction of a classification model for dementia among Brazilian adults aged 50 and over.Frontiers in aging neuroscience · 2026Article
- Advancing mental health diagnostics: a review on the role of smartphones, wearable devices, and artificial intelligence in depression and anxiety detection.Biomedical engineering letters · 2025Review
- A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer's Disease and Related Dementias.medRxiv : the preprint server for health sciences · 2025Article
- Integrated Multi-Omics Analysis and Cross-Model Validation Reveal Mitochondrial Signatures in Alzheimer's Disease.CNS neuroscience & therapeutics · 2025Article
- Dementia-related volumetric assessments in neuroradiology reports: a natural language processing-based study.BMJ open · 2025Article
- A novel interpreted deep network for Alzheimer's disease prediction based on inverted self attention and vision transformer.Scientific reports · 2025Article
- Using machine learning and electronic health record (EHR) data for the early prediction of Alzheimer's Disease and Related Dementias.The journal of prevention of Alzheimer's disease · 2025Article
- Contribution and legacy: a qualitative study of older people's attitudes about sharing their routinely collected health data for research purposes in New Zealand.BMC medical ethics · 2025Article
- Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging-based ATN biomarkers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Cognitive performance classification of older patients using machine learning and electronic medical records.Scientific reports · 2025Article
- A roadmap to precision medicine through post-genomic electronic medical records.Nature communications · 2025Review
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 1 institution in 1 country.
Funding
Abstract
objectiveAlzheimer disease (AD) is the most common cause of dementia, a syndrome characterized by cognitive impairment severe enough to interfere with activities of daily life. We aimed to conduct a systematic literature review (SLR) of studies that applied machine learning (ML) methods to clinical data derived from electronic health records in order to model risk for progression of AD dementia. MATERIALS AND
methodsWe searched for articles published between January 1, 2010, and May 31, 2020, in PubMed, Scopus, ScienceDirect, IEEE Explore Digital Library, Association for Computing Machinery Digital Library, and arXiv. We used predefined criteria to select relevant articles and summarized them according to key components of ML analysis such as data characteristics, computational algorithms, and research focus.
resultsThere has been a considerable rise over the past 5 years in the number of research papers using ML-based analysis for AD dementia modeling. We reviewed 64 relevant articles in our SLR. The results suggest that majority of existing research has focused on predicting progression of AD dementia using publicly available datasets containing both neuroimaging and clinical data (neurobehavioral status exam scores, patient demographics, neuroimaging data, and laboratory test values). DISCUSSION: Identifying individuals at risk for progression of AD dementia could potentially help to personalize disease management to plan future care. Clinical data consisting of both structured data tables and clinical notes can be effectively used in ML-based approaches to model risk for AD dementia progression. Data sharing and reproducibility of results can enhance the impact, adaptation, and generalizability of this research.
Indexed as
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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.