Kwon JM, et al. – Researchers developed and validated deep-learning–based out-of-hospital cardiac arrest prognostic system (DCAPS) for predicting neurologic recovery and survival to discharge. From the Korea out-of-hospital cardiac arrest (OHCA) registry, they identified 36,190 patients who experienced return of spontaneous circulation (ROSC) after OHCA and divided them into a set of 28,045 subjects for derivation data and 8,145 subjects for validation data. Neurologic recovery and survival to discharge of OHCA patients was accurately predicted using the DCAPS. Furthermore, it was found to be superior to the conventional method and other machine-learning methods.