MODILM: towards better complex diseases classification using a novel multi-omics data integration learning model

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 data with v...

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Detalles Bibliográficos
Autores principales: Zhong, Yating, Peng, Yuzhong, Lin, Yanmei, Chen, Dingjia, Zhang, Hao, Zheng, Wen, Chen, Yuanyuan, Wu, Changliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161645/
https://www.ncbi.nlm.nih.gov/pubmed/37147619
http://dx.doi.org/10.1186/s12911-023-02173-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161645/
https://www.ncbi.nlm.nih.gov/pubmed/37147619
http://dx.doi.org/10.1186/s12911-023-02173-9

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