Article intro - Machine learning in surgical robotics
"A review on machine learning in flexible surgical and interventional robots: Where we are and where we are going" written by Di Wu, Renchi Zhang, Ameya Pore, Diego Dall’Alba, Xuan Thao Ha, Zhen Li, Yao Zhang, Fernando Herrera, Mouloud Ourak, Wojtek Kowalczyk, Elena De Momi, Alícia Casals, Jenny Dankelman, Jens Kober, Arianna Menciassi, Paolo Fiorini and Emmanuel Vander Poorten appeared in Biomedical Signal Processing and Control 93 (2024) 106179. A B S T R A C T Minimally Invasive Procedures (MIPs) emerged as an alternative to more invasive surgical approaches, offering patient benefits such as smaller incisions, less pain, and shorter hospital stay. In one class of MIPs, where natural body lumens or small incisions are used to access deeper anatomical locations, Flexible Surgical and Interventional Robots (FSIRs) such as catheters and endoscopes are widely used. Due to their flexible and compliant nature, FSIRs can be inserted via natural orifices or small incisions, then
