Authors: Nisha Prabhakar
Abstract: The human microbiome, consisting of trillions of microorganisms inhabiting various body sites, plays a critical role in health and disease. Recent advances in high-throughput sequencing and metagenomics have generated vast datasets characterizing the complex microbial communities and their functional capabilities. However, the intricate interactions between microbiota, host physiology, and environmental factors pose significant challenges to data interpretation and the extraction of actionable insights. Artificial intelligence (AI), particularly machine learning, offers powerful computational tools to analyze complex, high-dimensional microbiome data, identify novel patterns, predict disease associations, and inform personalized therapeutic strategies. This paper explores AI-driven approaches to deciphering the human microbiome, including data integration techniques, predictive modeling, challenges in microbiome research, and future perspectives for leveraging AI to transform microbiome science and precision medicine.
DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.560
