Makina öğrenimi ile hasta bekleme sürelerinin tahmini

Accurately predicting waiting times can increase patient satisfaction and enable staff members to more accurately evaluate and respond to patient flow. In this study, we examined the applicability of the machine learning model to estimate waiting times in a blood collection unit. The blood collection units of hospitals are the places where the patient density is the highest. Because the patients who go to different outpatient clinics of the hospital come to the blood collection units to perform an examination and give blood or different tests. In this study, the patient records when he comes to the blood collection unit via a kiosk (philerobo artificial intelligence blood collection unit management system). Then they wait in the waiting room and the system calls the patient when the time comes. In our study, our model estimates the waiting time of artificial Neural Networks algorithm by considering some parameters (Arrival Time, Day of Week, Phlebotomists Count, Current Patient Duration, Waiting Patient Count with priority, Waiting Patient Count with the Same Priority, Incoming Patient Count, Outgoing Patient Count and patient priority) how long it will wait inside when the patient enters the kiosk. As a result of this, we aimed to predict how long the next patient will wait in the waiting room and to inform the patient.