ArticleCommunications medicine2023
Integrated algorithm combining plasma biomarkers and cognitive assessments accurately predicts brain β-amyloid pathology.
Article in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer's Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges.Sensors (Basel, Switzerland) · 2026Pooled it
- Neurofilament Light Chain (NfL) in Neurodegenerative Diseases: Biological and Clinical Significance, Multi-Omics Integration, and AI-Driven Biomarker Modeling for Precision Therapy.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Advancing Alzheimer's disease research in China: insights, innovations, and future directions from the chinese preclinical Alzheimer's disease study (CPAS).Molecular psychiatry · 2026Review
- Blood biomarkers to improve dementia diagnostic accuracy: a cross-sectional analysis.BMC geriatrics · 2026Article
- Substituting blood-based biomarkers for imaging measures in Alzheimer's disease studies: implications for sample size and bias.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Clinical impact of the Alzheimer's Disease Neuroimaging Initiative: A review of studies using ADNI data (2023 to June 2025).Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Derivation and validation of a new prediction score for bacteremia in the emergency department.Scientific reports · 2026Article
- MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.Brain topography · 2026Article
- AD diagnosis model based on fusion of heterogeneous brain imaging and genomic data.Frontiers in neuroscience · 2026Article
- Substituting Blood-Based Biomarkers for Imaging Measures in Alzheimer's Disease Studies: Implications for Sample Size and Bias.medRxiv : the preprint server for health sciences · 2025Article
- Frequency of Microvascular Pathology and Hippocampal Atrophy on Magnetic Resonance Imaging in a Community Study of Alzheimer's Disease with Blood-Based Biomarkers.Annals of neurology · 2025Article
- Predicting brain amyloid load with digital and blood-based biomarkers.Alzheimer's research & therapy · 2025Article
- Prediction Model and Nomogram for Amyloid Positivity Using Clinical and MRI Features in Individuals With Subjective Cognitive Decline.Human brain mapping · 2025Article
- Validation of the robustness of blood-based biomarkers for predicting amyloid-β positivity in Chinese populations.Frontiers in aging neuroscience · 2025Article
- Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning.Frontiers in aging neuroscience · 2025Article
- Construction of a prediction model for Alzheimer's disease using an AI-driven eye-tracking task on mobile devices.Aging clinical and experimental research · 2024Article
- Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids.World journal of pediatrics : WJP · 2024Article
- Consensus on rapid screening for prodromal Alzheimer's disease in China.General psychiatry · 2024Review
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate prediction of cerebral amyloidosis with easily available indicators is urgently needed for diagnosis and treatment of Alzheimer's disease (AD).
methodsWe examined plasma Aβ42, Aβ40, T-tau, P-tau181, and NfL, with APOE genotypes, cognitive test scores and key demographics in a large Chinese cohort (N = 609, aged 40 to 84 years) covering full AD spectrum. Data-driven integrated computational models were developed to predict brain β-amyloid (Aβ) pathology.
resultsOur computational models accurately predict brain Aβ positivity (area under the ROC curves (AUC) = 0.94). The results are validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Particularly, the models have the highest prediction power (AUC = 0.97) in mild cognitive impairment (MCI) participants. Three levels of models are designed with different accuracies and complexities. The model which only consists of plasma biomarkers can predict Aβ positivity in amnestic MCI (aMCI) patients with AUC = 0.89. Generally the models perform better in participants without comorbidities or family histories.
conclusionsThe innovative integrated models provide opportunity to assess Aβ pathology in a non-invasive and cost-effective way, which might facilitate AD-drug development, early screening, clinical diagnosis and prognosis evaluation.
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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.