ArticleBioengineering (Basel, Switzerland)2025
A Machine Learning-Based Diagnostic Nomogram for Moyamoya Disease: The Validation of Hypoxia-Immune Gene Signatures.
Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Molecular and multimodal biomarkers in Moyamoya disease: from pathogenic mechanisms to clinical translation.European journal of medical research · 2026Review
- Delayed Intracerebral Hemorrhage 15 Years After Indirect Revascularization in Moyamoya Disease: A Case Report and Review of the Literature.Brain sciences · 2025Article
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Authors and funding
6 authors.
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Abstract
Moyamoya disease (MMD) is a cerebrovascular disease which can result in severe strokes. However, its etiology is still unknown. We analyzed gene expression datasets from 36 MMD patients and 24 controls to identify differentially expressed genes. Using weighted gene co-expression network analysis and databases such as KEGG, we identified hypoxia-immune-related genes. These genes were further refined through machine learning algorithms. The diagnostic value was confirmed using an external dataset, and a diagnostic nomogram was constructed. Additionally, gene set enrichment analysis was conducted, and a competitive endogenous RNA (ceRNA) network was built to predict potential therapeutic targets. Our study identified
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