A language model can be used to predict the next word during authoring, to\ncorrect spelling or to accelerate writing (e.g., in sms or emails). Language\nmodels, however, have only been applied in a very small scale to assist\nphysicians during authoring (e.g., discharge summaries or radiology reports).\nBut along with the assistance to the physician, computer-based systems which\nexpedite the patient's exit also assist in decreasing the hospital infections.\nWe employed statistical and neural language modeling to predict the next word\nof a clinical text and assess all the models in terms of accuracy and keystroke\ndiscount in two datasets with radiology reports. We show that a neural language\nmodel can achieve as high as 51.3% accuracy in radiology reports (one out of\ntwo words predicted correctly). We also show that even when the models are\nemployed only for frequent words, the physician can save valuable time.\n