ArticleAlzheimer's & dementia (Amsterdam, Netherlands)
Dimensional clinical phenotyping using
Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- Predicting hospice eligibility among dementia patients using language models.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach.BMC psychiatry · 2025Article
- Dimensional Measures of Psychopathology in Children and Adolescents Using Large Language Models.Biological psychiatry · 2024Article
- Dimensional clinical phenotyping usingAlzheimer's & dementia (Amsterdam, Netherlands)Article
- Association of RDoC dimensions withAlzheimer's & dementia (Amsterdam, Netherlands)Article
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11 authors.
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Abstract
Introduction: Transdiagnostic dimensional phenotypes are essential to investigate the relationship between continuous symptom dimensions and pathological changes. This is a fundamental challenge to Methods: We adapted well-validated methodologies to compute National Institute of Mental Health Research Domain Criteria (RDoC) scores using natural language processing (NLP) from electronic health records (EHRs) obtained from Results: Our results confirm an association of EHR-derived cognitive scores with neuropathological findings. Notably, higher neuropathological load, particularly neuritic plaques, was associated with higher cognitive burden scores in the frontal (ß = 0.38, Discussion: This proof-of-concept study supports the validity of NLP-based methodologies to obtain quantitative measures of RDoC clinical domains from
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