Rodney A. Gabriel
University of California San Diego, UC San Diego Health System
Papers
2
Total Citations
95
H-Index
2
About
Rodney A. Gabriel is a leading voice in the intersection of anesthesiology, perioperative medicine, and data science. His research focuses on leveraging machine learning to enhance surgical efficiency and developing multimodal analgesia protocols to improve patient outcomes. Gabriel’s most impactful work, "A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery" (2019), has garnered 91 citations, demonstrating his pioneering role in applying predictive analytics to optimize operating room logistics. This contribution addresses a critical bottleneck in surgical care, offering data-driven solutions for resource allocation. Additionally, his 2024 study on robot-assisted laparoscopic nephrectomy examines the implementation of an acute pain service-driven multimodal analgesia protocol with intrathecal morphine, comparing its effectiveness against traditional surgeon-driven approaches. This work underscores his commitment to advancing perioperative pain management and patient recovery. Gabriel’s research not only bridges clinical practice with computational innovation but also provides actionable insights for improving surgical workflows and postoperative care. His contributions are essential reading for clinicians and researchers seeking to integrate machine learning and evidence-based pain strategies into modern surgical settings.
Research Focus
Key Achievements
Top Papers
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- 2