Congress:
ECR25
Poster Number:
C-18295
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
M. B. Bergan, M. Larsen, J. Gjesvik, Å. S. Holen, N. Moshina, T. Hovda, H. W. Koch, M. A. Martiniussen, S. Hofvind; Oslo/NO
Disclosures:
Marie Burns Bergan:
Nothing to disclose
Marthe Larsen:
Nothing to disclose
Jonas Gjesvik:
Nothing to disclose
Åsne Sørlien Holen:
Nothing to disclose
Nataliia Moshina:
Nothing to disclose
Tone Hovda:
Nothing to disclose
Henrik Wethe Koch:
Nothing to disclose
Marit Almenning Martiniussen:
Nothing to disclose
Solveig Hofvind:
Nothing to disclose
Keywords:
Breast, Mammography, Computer Applications-Detection, diagnosis, Cancer
Almost 98% of the screen-detected cancers with an interpretation score of ≥3 by both radiologists were identified by AI at a 10% threshold, while 91% of screen-detected cancers with a score of ≥3 by one radiologist were identified. At a 10% threshold AI identified 35% of the interval cancers interpreted negative by both radiologists.