Congress:
ECR25
Poster Number:
C-28099
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
D. Pisarcik, M. Kissling, J. Heimer, R. Kubik-Huch, A. Euler; Baden/CH
Disclosures:
Dusan Pisarcik:
Other: Sirius Medical
Marc Kissling:
Nothing to disclose
Jakob Heimer:
Nothing to disclose
Rahel Kubik-Huch:
Nothing to disclose
Andre Euler:
Speaker: Siemens
Keywords:
Artificial Intelligence, Mammography, Ultrasound, Biopsy, Cancer, Neoplasia
Previous research primarily evaluated readability and accuracy based on expert feedback, while our study uniquely aimed to assess the interpretability and perception of various AI-translated mammography and sonography reports, covering benign to potentially malignant pathologies. Using a patient survey, we evaluated the comprehensibility of diagnoses, follow-up procedures, and conveyed empathy.