August 20, 2025Frontiers in PharmacologyOpen Access

Multimodal integration strategies for clinical application in oncology

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Multimodal integration enhances patient diagnosis and treatment outcomes, leveraging diverse data sources.
Analysis demonstrated that AI methods effectively integrate clinical, genomic, and imaging data types.
Current methodologies include machine learning, multi-omics, and representation learning for various data modalities.
The findings highlight both the clinical potential and ongoing challenges in integrating multiple data types for oncology.

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Analysis reveals multimodal integration improves cancer diagnosis and treatment outcomes, suggesting AI's role is crucial.

Zhang et al. (2025) studied this question.

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