 This research paper examined the use of electroencephalogram, e.g., data to predict the outcome of patients with disorders of consciousness, DOC. Three different models were developed using different combinations of e.g., and clinical data to predict the coma recovery scale revised, CRSR, score at discharge. The best model had a median absolute test error of 4.54, 3.39, and 3.16 for the e.g., clinical and hybrid models respectively. This shows that e.g., data can provide valuable information about the patient's progression towards recovery from their DOC. Additionally, the hybrid model showed improved performance compared to the other models when it came to predicting whether or not the patient would exit an unresponsive wakefulness state. Overall, this research demonstrates the potential of e.g., data to improve the accuracy of predictions regarding the progression of patients with DOC. This article was authored by Pier Giuseppe Liuzzi, Antonello Grippo, Silvia Campignini, and others. We are article.tv. Links in the description below.