Genome Data‐Based Explainable Recommender Systems

Genomics and personalized medicine have revolutionized healthcare by allowing doctors to customize treatments to individual genetic profiles. Genomic recommender systems utilize advanced machine learning techniques to analyze genomic data and provide personalized recommendations for various applications in healthcare and genetics. These systems make recommendations and explain why specific treatments or medications are suggested, giving clarity to patients and building trust in the recommendation. Achieving transparency and interpretability in these systems is crucial to ensure that patients have confidence in their decisions based on their genetic data. This chapter comprehensively reviews existing research in this field, discusses its challenges, and highlights future directions for advancements in explainable genomic recommendation systems.