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As the healthcare industry continues adjusting to the increasing diagnosis of lifestyle-related diseases and demand for affordable care, effective surgical procedures assisted by robotic devices and a decline in treatment costs look promising. Next-generation surgical robotic technology platforms complement and extend surgeons’ ability to minimize surgical variability, a key factor driving adoption of robotic-assisted surgical device (RASD) platforms among hospitals, as now surgeons can perform complex tasks with greater control and less strain while ensuring patient safety.

The need to gain experience before robotic-assisted surgery remains debatable; however, the transition from a laparoscopic surgeon to a robotic surgeon is associated with a shorter learning period. Hence, several medical and research institutes in the United States and Europe now offer robotic surgery training programs to ensure more surgeons have the expertise and skills needed, but with a shorter learning curve.

With the advancement of digital and analytical technologies, deployment of artificial intelligence (AI) technologies, including machine learning and machine vision, in next-generation surgical platforms enables the systems to offer insights to surgeons based on analysis of the data collected. Moreover, haptic feedback signals when the pressure threshold is reached as a way to prevent damaging anatomical structures.