ArticleNature medicine2024
AI-based differential diagnosis of dementia etiologies on multimodal data.
Article in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 3 of them syntheses that pooled it.
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Who cites it
78 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.Journal of medical Internet research · 2026Pooled it
- Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion.Frontiers in dementia · 2026Pooled it
- Reflections on dynamic prediction of Alzheimer's disease: advancements in modeling longitudinal outcomes and time-to-event data.BMC medical research methodology · 2025Pooled it
- Evaluating digital cognitive tests for clinical use in Alzheimer's disease: A novel framework and scoping review.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Agentic AI for scaling diagnosis and care in neurodegenerative disease.Nature aging · 2026Review
- Article
- Robust Longitudinal Dementia Prediction under Systemic Missingness via Hierarchical Fusion and Test-Time Adaptation.medRxiv : the preprint server for health sciences · 2026Article
- Artificial Intelligence That Changes Clinical Neurology Practice: Translating Algorithms Into Actionable Care.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Advances in artificial intelligence for neuroimaging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Development of a multimodal large language model for early warning and diagnosis of chronic ocular GVHD.NPJ digital medicine · 2026Article
- Development and validation of a Cog-Free risk predicting tool for dementia in a community setting.General psychiatry · 2026Article
- Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism.Annals of neurology · 2026Article
- Homeostatic dendritic neuron based on co-integrated volatile and non-volatile memristors for neuromorphic processing.Nature communications · 2026Article
- A deep joint-learning proteomics model for diagnosis of six conditions associated with dementia.Nature medicine · 2026Article
- Patients' and care partners' views on communicating the cause of dementia and related uncertainties: A qualitative study.Journal of Alzheimer's disease : JAD · 2026Article
- GPND-AI NULISA: A 15-Protein AI classifier for diagnosis and co-pathology profiling across neurodegenerative diseases.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Predictive Cellular Signatures from Live Human Motor Neurons Distinguish TDP-43 ALS and Enable ALS Subtype Stratification.bioRxiv : the preprint server for biology · 2026Article
- 3D foundation model for generalizable disease detection in head computed tomography.Nature biomedical engineering · 2026Article
- Multimodal deep learning with missing data robustness for enhanced early diagnosis of coronary artery disease using CCTA, clinical, and ECG data.BMC medical informatics and decision making · 2026Article
18 more citing papers are in PubMed but not listed here.
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Authors and funding
38 authors.
Funding
Abstract
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
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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.