Daniele De Massari

Stryker (Netherlands), Stryker (United States)

Papers

Total Citations

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About

Daniele De Massari is a leading researcher at the intersection of orthopedic surgery and data science, with a primary focus on optimizing robotic-assisted total knee arthroplasty (TKA). His major contributions lie in developing predictive models to enhance surgical efficiency and patient-specific outcomes. In his highly cited 2022 work, he pioneered the first predictive model for robotic-assisted TKA operating time using demographic data and CT imaging, achieving 20 citations. He further advanced this field in 2023 by leveraging machine learning on large, real-world datasets to forecast operative duration, demonstrating how artificial intelligence can improve staff utilization and operating room efficiency—a study that has garnered 16 citations. Most recently, in his 2024 publication, De Massari challenges the traditional neutral mechanical alignment paradigm, advocating for a patient-specific target approach informed by three-dimensional analysis. His work bridges the gap between classical orthopedic principles and modern, individualized surgical planning, positioning him as a key voice in the evolution of precision arthroplasty. With a growing citation impact, De Massari’s research is shaping how surgeons leverage data-driven tools to improve both procedural efficiency and long-term patient outcomes.