The Clinical Trajectory of AI in Precision Medicine: A Science Mapping Analysis of Multi-Omics Research

The convergence of artificial intelligence (AI) and multi-omics technologies is fundamentally reshaping precision medicine, enabling the transition from static single-gene profiling to dynamic, systems-level healthcare. As the volume of research at this intersection accelerates, there is a critical need to systematically map the intellectual landscape to understand its structural evolution, identify core translational domains, and highlight emerging clinical frontiers. To delineate the conceptual architecture of this field, a comprehensive bibliometric and science mapping analysis was conducted. A curated dataset comprising ۱,۴۳۹ relevant works was extracted from the OpenAlex database. Utilizing VOSviewer, a keyword co-occurrence network and chronological overlay visualizations were generated to analyze thematic clustering, interdisciplinary connectivity, and temporal research trends. The network analysis partitioned the field into six distinct thematic clusters: Precision Healthcare Implementation, Biomarker & Systems Biology, Clinical Pathology & Oncology, Computational Drug Development, Multi-Omics Foundations, and Core AI Algorithmic Infrastructure. Cross-cluster connectivity revealed oncology as the primary vanguard for clinical translation. Chronological mapping demonstrated a definitive evolutionary shift in the literature. Foundational research (pre-۲۰۲۴) heavily prioritized establishing algorithmic and bioinformatic pipelines, whereas recent hotspots (averaging publication years ۲۰۲۵ and later) focus on clinical applications, targeted drug discovery, and next-generation biocomplexity, including the microbiome and tumor microenvironment. The interdisciplinary domain of AI-integrated multi-omics is rapidly maturing from an exploratory, methodology-centric science into an applied clinical discipline. While robust in silico frameworks have been established, a significant translational gap remains. Realizing the full clinical potential of these technologies will require future research to prioritize explainable AI (XAI), mandate diverse cohort datasets, and actively pursue large-scale, prospective clinical validation of computational biomarkers.

کلیدواژه ها:

Precision Medicine ، Multi-omics ، Artificial Intelligence ، Bibliometric Analysis ، Science Mapping ، Systems Biology