Discussion
postoperative infections, infections
CNS INFECTIONS, INFECTIONS, POSTOPERATIVE INFECTION
In this observational cohort study, we applied a deep learning framework for the prediction of infections in elderly patients after surgery. We demonstrated that an artificial-intelligence model using deep learning neural networks can achieve a promising prediction of postoperative infections in elderly patients. Predictive performance was improved further when the deep learning-based model was derived with risk factors relevant to baseline clinical characteristics/measurements and surgery in combination. Our work indicates that using deep learning may guide clinical practice to prevent infections following surgery in elderly although further work is needed to validate machine learning for it to be a potential and ubiquitous integral part of routine clinical use for elderly surgical patients.Deep learning is the process of training a neural network (a large mathematical function with millions of parameters) to perform a given task [As elderly patients are the most frequent users of operative resources and are also the most vulnerable to postoperative infections, it is important for clinicians to gauge risk factors preoperatively [The strength of this study was that it collected a relatively large group of elderly patients undergoing elective surgery in multiple institutions. In addition, the baseline parameters and surgery-relevant characteristics applied in the deep learning model dovetail with a customary clinical workflow that can be routinely collected. However, this study is not without limitations. Clinical uses of AI have aroused skepticism including the difficulty of explaining the complex computational steps leading to a machine-generated clinical determination [