Daniel C. Thomas

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About

Daniel C. Thomas is a leading thoracic surgeon whose research focuses on the adoption and optimization of robotic-assisted thoracoscopic surgery (RobATS) for lung cancer treatment. His major contributions center on defining the learning curve for robotic lobectomy and validating its outcomes against traditional approaches. In his seminal 2018 study, "Defining the learning curve in robot-assisted thoracoscopic lobectomy," Thomas established that surgeons achieve proficiency after approximately 20 cases, a finding that has guided training protocols worldwide (42 citations). His subsequent analysis of "Robotic-Assisted Lobectomies in the National Cancer Database" (25 citations) provided critical real-world evidence that RobATS lobectomy is safe and effective across diverse hospital settings, accelerating its adoption in thoracic oncology. Thomas’s work has been instrumental in demystifying robotic surgery, demonstrating that with proper training, it can match or exceed outcomes of conventional video-assisted techniques. His research continues to shape best practices for minimally invasive lung cancer surgery, making him a key voice in the transition toward robotic-assisted approaches.