MODILM: towards better complex diseases classification using a novel multi-omics data integration learning model
Abstract Background Accurately classifying complex diseases is crucial for diagnosis and personalized treatment. Integrating multi-omics data has been demonstrated to enhance the accuracy of analyzing and classifying complex diseases. This can be attributed to the highly correlated nature of the dat...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-05-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-023-02173-9 |