eScholarship
metadata only
Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis
OBJECTIVES: Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether un
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Revising the ABIDE MCI to dementia prediction model for automated cerebrospinal fluid assays#8121
- Latent Profiles on the Intelligence and Development Scales – 2 and their Relationship with Classifications of Dyslexia and ADHD#1148188
- Toward Generalizable Cognitive Impairment Detection with Speech-Based Multimodal Large Language Models#394398
- Latent Profiles on the Intelligence and Development Scales – 2 and their Relationship with Classifications of Dyslexia and ADHD#236839
- Multimodal EEG and explainable machine learning characterize neuroticism-related neurodynamic heterogeneity in mild cognitive impairment during visuospatial working memory.#445971
Record · ID 1448991
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive