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Minimally invasive gastrectomy (MIG) has gained in popularity, since it is feasible, safe and oncologically comparable to open gastrectomy, while morbidity and duration of hospitalization are reduced, quality of life is increased, and conversion rate is low. However, several challenges are faced during MIG, such as impaired depth perception and limited range of motion of instrument tips. Robot-Assisted Minimally Invasive Gastrectomy (RAMIG) can potentially overcome these challenges, while providing comparable results regarding safety, technical feasibility, morbidity and oncological effectiveness. However, the techniques and outcomes of RAMIG vary in literature, which can partly be explained by lack of uniform definitions of postoperative outcomes that would allow international comparison. Furthermore, RAMIG is technically demanding and therefore associated with a learning curve. To fa
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