**5.2 Application in orthopedic surgery and orthopedic trauma**

The incorporation of AI to assist in the surgical procedure has aroused great interest at present. For example, AI has been used as an assistant for image segmentation. The algorithm is able to differentiate the image fragment that is a healthy tissue from

the mass to be studied or removed. This facilitates a time-consuming task in a fast and automated way [20].

AI has also been used in algorithms for predicting outcomes or costs associated with the surgical procedure. The DL is able to process a large amount of input data (age, comorbidities, and gender) and generate a certain outcome with predictive capacity (cost of hospitalization). For example, one paper analyzed 175,042 patients undergoing primary total knee replacement surgery with 15 preoperative variables, being able to estimate length of hospital stay and hospital costs, adjusting certain comorbidities [21].

Furthermore, AI has been used to help decide on the appropriateness of performing a surgical intervention, for example, to preoperatively assess the risk of death or complication. This would serve to provide the surgeon and patient with better information when deciding on the optimal management option [22].
