Congress:
ECR25
Poster Number:
C-24137
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
D. Männle, M. Langhals, N. Santhanam, C. G. Cho, H. Wenz, C. Groden, F. Siegel, M. E. Maros; Mannheim/DE
Disclosures:
David Männle:
Nothing to disclose
Martina Langhals:
Nothing to disclose
Nandhini Santhanam:
Nothing to disclose
Chang Gyu Cho:
Nothing to disclose
Holger Wenz:
Nothing to disclose
Christoph Groden:
Nothing to disclose
Fabian Siegel:
Nothing to disclose
Máté Elöd Maros:
Consultant: Non-related consultancy EppData GmbH Consultant: Non-related consultancy Siemens Healthineers AG
Keywords:
Artificial Intelligence, Computer applications, Neuroradiology brain, CT, CT-Angiography, RIS, Computer Applications-General, Technology assessment, Ischaemia / Infarction
Out of 206 cases, 99 were female (48.0%; median_age: F=79.7 vs. M=73.2; range=21.7-95.9yrs; p=7.5x10^-4). Non-contrast cranial CT was performed in 155 (75.2%) remaining also received CTA (n=47;22.8%) and/or CTP (n=21;10.2%). The median word count of findings and impressions were 142 (range=5-473) and 30 (range=5-184), respectively; resulting in ~600-800 tokens/report. Thus, limiting maximal context length to ~10-12 reports for compatibility with older-generation LLMs. Overall, 12400 (8x2x31x25) configurations of LLM-ICL-strategies were validated. The overall best test-performance was shown by llama3.1[:70b] and mixtral[8x7b].