Artificial Intelligence Applications in Microbiome Research for Prostate Cancer: A Narrative Review - Muhammad Rizki Fadil; Fabian Gamal Sutrisno; Archie Fontana Iskandar (Rifa'Institute, 2026)
Introduction: Prostate cancer is one of the most common malignancies in men worldwide and exhibits substantial biological heterogeneity, creating challenges in diagnosis, prognosis, and treatment selection. Artificial intelligence has emerged as a promising approach for analyzing complex microbiome datasets characterized by high dimensionality and biological variability. Objective: This narrative review aims to summarize current evidence regarding the application of artificial intelligence in microbiome research related to prostate cancer, with emphasis on biological insights, analytical approaches, current challenges, and future research directions. Method: A narrative review was conducted through a literature search of scientific databases using keywords related to prostate cancer, microbiome, microbiota, machine learning, artificial intelligence, and deep learning. Relevant original studies, review articles, and methodological papers were identified through database searching, citation tracking, and manual reference screening. The selected literature was synthesized narratively according to major thematic areas. Result and Discussion: Current evidence suggests that alterations in microbiome composition may be associated with prostate cancer through mechanisms involving immune modulation, microbial metabolites, inflammation, hormonal regulation, and host-environment interactions. Artificial intelligence, particularly machine learning, has been increasingly applied to microbiome analysis for feature selection, pattern recognition, biomarker discovery, and predictive modeling. Algorithms such as Random Forest, Least Absolute Shrinkage and Selection Operator, Extreme Gradient Boosting, and deep learning have showed potential for extracting biologically relevant information from complex datasets and supporting precision oncology approaches. Conclusions: The integration of artificial intelligence and microbiome research in prostate cancer represents a promising but still emerging field