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Unified Bayesian representation for high-dimensional multi-modal biomedical data for small-sample classification
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DOI：10.1016/j.engappai.2025.111887.png)
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Abstract
En 中文
The increasing availability of multi-modal medical data, including neuroimaging, genetic profiles, and clinical measurements, offers unprecedented opportunities for advancing disease diagnosis and prognosis. However, integrating these heterogeneous data sources poses significant challenges due to their high dimensionality, redundancy, and small sample sizes, which hinder the effectiveness of traditional machine learning models.
Keywords:
Bayesian modeling
Multi-modal data
Wide-data
Machine learning health applications
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