Anthony J. DeSantis

Papers

Total Citations

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About

Anthony J. DeSantis is a forward-thinking researcher at the intersection of machine learning and surgical science. His work centers on harnessing predictive analytics to transform perioperative care, with a particular focus on developing data-driven models that anticipate patient outcomes and optimize surgical decision-making. His most-cited paper, "The present and future state of machine learning for predictive analytics in surgery" (2020, 6 citations), provides a comprehensive roadmap for integrating artificial intelligence into clinical practice, highlighting both current capabilities and emerging challenges. This foundational review has been instrumental in shaping discussions around the ethical deployment of algorithms in high-stakes medical environments. DeSantis’s contributions extend beyond theoretical frameworks, as he actively explores how real-world surgical data can be leveraged to reduce complications and improve recovery trajectories. While his citation count reflects the early-stage nature of this rapidly evolving field, his work is gaining traction among clinicians and data scientists alike. By bridging the gap between complex computational methods and tangible surgical applications, DeSantis is helping to define a new era of evidence-based, technology-enhanced medicine—one where machine learning becomes a trusted partner in the operating room.