Florian Jungmann, B Kämpgen, F Hahn, D Wagner, P Mildenberger, C Düber, R Kloeckner
OBJECTIVE: During the COVID-19 pandemic, the number of patients presenting in hospitals because of emergency conditions decreased. Radiology is thus confronted with the effects of the pandemic. The aim of this study was to use natural language processing (NLP) to automatically analyze the number and distribution of fractures during the pandemic and in the 5 years before the pandemic. MATERIALS AND METHODS: We used a pre-trained commercially available NLP engine to automatically categorize 5397 radiological reports of radiographs (hand/wrist, elbow, shoulder, ankle, knee, pelvis/hip) within a 6-week period from March to April in 2015-2020 into "fracture affirmed" or "fracture not affirmed...
April 13, 2021: Skeletal Radiology