Explainable Artificial Intelligence for Precision Medicine and Multi-Omics Data Integration

Dear Colleagues,

Precision medicine is transforming healthcare by enabling prevention, diagnosis, prognosis, and treatment tailored to individual patient characteristics. Advances in multi-omics, medical imaging, and electronic health records provide increasingly rich data for personalized decision-making. Artificial intelligence (AI) offers powerful approaches for integrating these heterogeneous data; however, limited interpretability and clinical translation remain major challenges. This Special Issue on “Explainable Artificial Intelligence for Precision Medicine and Multi-Omics Data Integration” will focus on original research and comprehensive reviews addressing interpretable and clinically relevant AI approaches. Topics include, but are not limited to, the following:

• Explainable AI for precision medicine: Interpretable machine learning and deep learning for personalized diagnosis, prognosis, and treatment.
• Multi-omics data integration: AI-driven integration of genomic, transcriptomic, proteomic, metabolomic, and other molecular data.
• Multimodal precision medicine: Integration of multi-omics with medical imaging, electronic health records, and clinical information.
• Trustworthy and translational AI: Methods addressing interpretability, robustness, fairness, validation, and clinical implementation.

This Special Issue aims to bridge AI, biomedical data science, and precision medicine by highlighting approaches that transform complex biomedical data into interpretable and clinically actionable knowledge.

Dr. Ahmed Al Marouf
Guest Editor

Dr. Md Mozaharul Mottalib
Guest Editor Assistant

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