Artificial Intelligence in Urological and Reproductive Genomic Medicine

Genitourinary and reproductive diseases are driven by genetic variations, epigenetic dysregulation and disrupted genomic regulatory networks. The explosive growth of multi-omics data enables in-depth exploration of disease pathogenesis, yet the high dimensionality and complexity of these data pose major analytical challenges. Artificial intelligence (AI) has emerged as a powerful tool for mining genomic big data, interpreting genetic variants, integrating multi-omics profiles and constructing genetic risk prediction models. This Research Topic focuses on cutting-edge AI applications in genitourinary and reproductive genetics, aiming to advance intelligent, genetic research and translational medical practice through multidisciplinary collaboration.This Research Topic aims to explore the innovative applications and underlying technical mechanisms of artificial intelligence in genetic and translational research of urological and reproductive system diseases. It promotes interdisciplinary communication and cooperation between AI technologists and genetic and clinical researchers. Different from conventional clinical applications, this topic focuses on AI-driven genomic variant analysis, multi-omics data integration, genetic susceptibility identification, and genetic risk prediction of genitourinary and reproductive disorders. By summarizing cutting-edge advances and unresolved technical bottlenecks in AI-assisted genetic research, this Research Topic intends to provide novel insights for advancing intelligent precision genetics and translational development of urology and reproductive medicine.We welcome submissions of Original Research, Review, Mini-Review, Meta-analyses, Opinion, Clinical Trials, as well as Case Reports focusing on, but not strictly limited to the following AI-enabled genetic and genomic research in urological and reproductive system diseases:• AI-assisted identification and functional interpretation of disease-related genetic variants in adrenal and urinary system disorders• Intelligent mining and integrative analysis of multi-omics data for renal and urinary tract disease genetic mechanisms• AI-driven screening of genetic biomarkers and genetic risk stratification for benign and malignant prostate diseases• Intelligent epigenetic profiling and gene regulatory network analysis for testicular and male reproductive system disorders• AI-based exploration of genetic determinants underlying gonadal and reproductive system developmental abnormalities and pathological degeneration• AI applications in deciphering genetic and molecular mechanisms of refractory urogenital and reproductive diseases and supporting pharmacogenomic researchAll submitted manuscripts must have a clear genetic or genomic component. Purely clinical, epidemiological, or observational studies without a genetic or genomic foundation are outside the scope of this Research Topic. Submissions based on computational or AI-driven re-analysis of public datasets must include independent validation (clinical cohort or in vitro/in vivo experiments) or demonstrate substantial methodological novelty. Topic editors: Jiaju Xu, Yibo He, Ningjing Ou Source: https://www.frontiersin.org/research-topics/82465/artificial-intelligence-in-urological-and-reproductive-genomic-medicine