Hemodialysis, a renal replacement treatment for end-stage renal failure, relies heavily on the proper functioning of the dialysis machine. Timely detection and handling of dialysis machine alarms are important to ensure the safety of dialysis treatment. This study proposes a method for recognizing dialysis machine alarms using a convolutional neural network (CNN). A dataset of dialysis machine alarm light images was created through a multicenter collaboration, which was used to train the YOLOv5 model. The study shows that the average recognition precision, recall, and mAP@0.5 for each warning ...
