Ya Gao
Papers
1
Total Citations
1
H-Index
1
About
Ya Gao is a prominent figure in evidence-based medicine and bibliometric analysis, with a particular focus on the intersection of artificial intelligence and clinical research. Her work systematically maps the global research landscape of AI in randomized controlled trials, providing critical insights into how machine learning and deep learning technologies are being integrated into medical study designs. Gao’s 2022 bibliometric study, which has garnered significant attention, offers a comprehensive overview of AI-related RCT output, highlighting trends, gaps, and opportunities for Chinese scholars and international collaborators alike. By synthesizing vast amounts of publication data, she has helped clarify the evolving role of AI in evidence generation, from diagnostic algorithms to predictive modeling in clinical settings. Her contributions are especially valuable for researchers seeking to understand the methodological rigor and translational potential of AI-driven trials. Gao’s work continues to shape how the scientific community evaluates the credibility and impact of artificial intelligence in medicine, making her a key voice in the ongoing dialogue between technology and clinical practice.
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