Shouhao Zhou
Papers
2
Total Citations
33
H-Index
2
About
Shouhao Zhou is a leading researcher at the intersection of health policy, surgical technology adoption, and predictive analytics in medicine. His work critically examines how hospitals make high-stakes capital investments, particularly in robotic surgical systems, revealing the complex economic and organizational factors that drive technology diffusion. Zhou’s landmark study on hospital decisions to purchase robotic systems (19 citations) provides essential insights into the non-clinical drivers of surgical innovation, influencing how administrators evaluate costly equipment. More recently, he has pioneered the application of machine learning to improve surgical efficiency, developing predictive models for operative time in metabolic and bariatric surgery (14 citations). This work directly addresses the operational challenges of operating room scheduling, offering data-driven tools to enhance resource allocation and patient care. By bridging health economics, technology assessment, and artificial intelligence, Zhou’s research is shaping both strategic hospital decision-making and the practical optimization of surgical workflows, making him a key voice in the future of evidence-based surgical management.
Research Focus
Key Achievements
Top Papers
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