Work

Pitfalls with anomaly detection for breast cancer risk prediction

Year: 2025

Type: conference-paper

Source: SPIE Medical Imaging: Computer-Aided Diagnosis

DOI: 10.1117/12.3047285

Authors: Tom Lucas Koller, Kai Geißler, Ani Ambroladze, Eva M. Fallenberg, Michael Ingrisch, Heba Amer, Phillip Seeböck, Georg Langs, Horst K. Hahn

Institutions: University of Bremen, Fraunhofer Institute for Digital Medicine, Technical University of Munich, Munich Center for Machine Learning, Ludwig-Maximilians-Universität München, Zagazig University, Medical University of Vienna

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4407489640

FWCI:

Cites: 13

Cited by:

Related to: 10