The study analyzed scientific texts based on a manually created database of synopses of theses in dentistry. The main goal was to structure medical texts into various topics by means of natural language processing techniques (topic modeling). Furthermore, a dynamic topic modeling showed the most popular in the field of dentistry over almost the last thirty years.
Keywords: ARTM; Dentistry; Machine Learning; Natural Language Processing; Topic Modeling; Unstructured Data.