Predicting estrogen receptor status from HE-stained breast cancer slides using artificial intelligence.

Saved in:
Bibliographic Details
Title: Predicting estrogen receptor status from HE-stained breast cancer slides using artificial intelligence.
Authors: Høibø M; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.; Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway., Spiske U; Department of Health Research, SINTEF Digital, Trondheim, Norway., Pedersen A; Application Solutions, Sopra Steria, Trondheim, Norway., Ytterhus B; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway., Akslen LA; Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, Bergen, Norway.; Department of Pathology, Haukeland University Hospital, Bergen, Norway., Wik E; Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, Bergen, Norway.; Department of Pathology, Haukeland University Hospital, Bergen, Norway., Askeland C; Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, Bergen, Norway.; Department of Pathology, Haukeland University Hospital, Bergen, Norway., Reinertsen I; Department of Health Research, SINTEF Digital, Trondheim, Norway.; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway., Smistad E; Department of Health Research, SINTEF Digital, Trondheim, Norway.; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway., Valla M; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.; Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Source: Frontiers in medicine [Front Med (Lausanne)] 2025 Jun 09; Vol. 12, pp. 1593143. Date of Electronic Publication: 2025 Jun 09 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
Description
ISSN:2296-858X
DOI:10.3389/fmed.2025.1593143