Explainable AI for Length of Stay prediction in a Critical Care Unit

Having the ability to predict a patient's length of stay (LOS) with accuracy during their visit to the intensive care unit (ICU) can be a valuable opportunity for enhancing hospital planning and efficient management of clinical resources. The goal of this project is to elucidate the decision-making process of the algorithm created by Tianjian Gao and Dr. Ying Ding, as well as to identify the most relevant patients and their associated risk scores, with a focus on the key factors contributing to their length of stay.