Algorithmic and user study of an autocompletion algorithm on a large medical vocabulary

► We describe an autocompletion algorithm for snomed ct medical on-tology. ► Our user study proves it saves significantly more keystrokes than baseline algorithm. ► We explain keystrokes savings by pointing at entropy patterns in terms in snomed ct. ► Computationally, computing the shortest successful query for this algorithm is NP-hard.