Towards an AI-based Genomic Medicine of Precision that Integrates Predictive and Explainable Knowledge Dimensions

• Óscar Pastor Universitat Politècnica de Valencia
• Salvador Navarro Universitat Politècnica de Valencia
• Alberto García Universitat Politècnica de Valencia
• Mireia Costa Universitat Politècnica de Valencia
• Ana León Universitat Politècnica de Valencia

DOI: https://doi.org/10.5753/cibse.2024.28467

Resumo

Understanding the human genome and deciphering the Language of Life is a grand challenge that modern sequencing technologies are making feasible by generating huge amounts of data whose correct interpretation has yet to be accomplished. To do it, two knowledge dimensions must be integrated: the predictive one, Machine Learning-oriented, that obtain accurate information from data, and the explainable one, Conceptual Modeling-based, that uses a symbolic representation to provide meaning to the data in order to understand and explain the semantics behind predictions. This position report discusses the problem, contextualizes it under a Life Engineering perspective, and it proposes how to face the design of AI-based data management platforms that follows the introduced ideas.

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