Deciding which patients should go into the intensive care unit (ICU) after surgery is a difficult call and typically made entirely at the surgeon's discretion. The result is that surgeons typically err on the side of caution by putting more post-operative patients in the ICU than necessary. To aid in better ICU decision-making, physicians at New York University Langone Hospital System (NYU Langone) developed a machine learning algorithm that combs through a patient's electronic medical record to identify relevant factors to determine if they needed the ICU after surgery.