Congress:
ECR25
Poster Number:
C-21584
Type:
Poster: EPOS Radiologist (scientific)
DOI:
10.26044/ecr2025/C-21584
Authorblock:
W. Pettit1, M. Ryan2, A. Raginis-Zborowska2, E. Compton2, A. Kumar1; 1Berkshire and Surrey/UK, 2Sydney/AU
Disclosures:
William Pettit:
Nothing to disclose
Melissa Ryan:
Employee: Annalise AI
Alicja Raginis-Zborowska:
Employee: Annalise AI
Emma Compton:
Employee: Annalise AI
Amrita Kumar:
Nothing to disclose
Keywords:
Artificial Intelligence, Oncology, Respiratory system, Plain radiographic studies, Computer Applications-Detection, diagnosis, Cancer
The purpose of this retrospective evaluation was to assess the performance and generalisability of an artificial intelligence (AI) tool (Annalise Enterprise v3.8) for identification of “clinically remarkable” (study contained findings indicative of urgent suspected lung cancer and/or clinically acute findings) chest radiographs in a clinical setting prior to clinical use. The project is a part of the UK national AI Diagnostic Fund where it was deployed on a regional level as part of 5 hospitals.