Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis.

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Title: Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis.
Authors: Cai L; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany., Pfob A; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany.; National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany., Barr RG; Department of Radiology, Northeast Ohio Medical University, Ravenna, OH., Duda V; Department of Gynecology and Obstetrics, University of Marburg, Marburg, Germany., Alwafai Z; Department of Gynecology and Obstetrics, University of Greifswald, Greifswald, Germany., Balleyguier C; Department of Radiology, Institut Gustave Roussy, Villejuif Cedex, France., Clevert DA; Department of Radiology, University Hospital Munich-Grosshadern, Munich, Germany., Fastner S; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany., Gomez C; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany., Goncalo M; Department of Radiology, University of Coimbra, Coimbra, Portugal., Gruber I; Department of Gynecology and Obstetrics, University of Tuebingen, Tuebingen, Germany., Hahn M; Department of Gynecology and Obstetrics, University of Tuebingen, Tuebingen, Germany., Kapetas P; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.; Breast Imaging Service, Department of Radiology, Memorial Sloan Kettering Cancer, New York, NY., Nees J; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany., Ohlinger R; Department of Gynecology and Obstetrics, University of Greifswald, Greifswald, Germany., Riedel F; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany., Rutten M; Department of Radiology, Jeroen Bosch Hospital, 's-Hertogenbosch, the Netherlands.; Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, the Netherlands., Stieber A; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany., Togawa R; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany., Sidey-Gibbons C; Health AI Innovation, Oracle Corporation, Austin, TX., Tozaki M; Department of Radiology, Sagara Hospital, Kagoshima, Japan., Wojcinski S; Department of Gynecology and Obstetrics, Breast Cancer Center, Klinikum Bielefeld, Bielefeld, Germany., Heil J; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany.; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany., Golatta M; Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg, Germany.; Breast Center Heidelberg, Hospital St Elisabeth, Heidelberg, Germany.
Source: Journal of clinical oncology : official journal of the American Society of Clinical Oncology [J Clin Oncol] 2025 Nov 10; Vol. 43 (32), pp. 3482-3493. Date of Electronic Publication: 2025 Aug 20.
Publication Type: Clinical Trial; Journal Article; Multicenter Study; Research Support, Non-U.S. Gov't
Journal Info: Publisher: American Society of Clinical Oncology Country of Publication: United States NLM ID: 8309333 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1527-7755 (Electronic) Linking ISSN: 0732183X NLM ISO Abbreviation: J Clin Oncol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1527-7755
DOI:10.1200/JCO-24-02681