Document is current
Any future updates will be listed below
-
Authors
Yamaguchi, Takeshi https://orcid.org/0000-0003-3306-314X
Koyama, Yoichi https://orcid.org/0000-0001-7435-1346
Inoue, Kenichi https://orcid.org/0000-0002-0501-9945
Ban, Kanako https://orcid.org/0000-0002-7244-2436
Hirokaga, Koichi https://orcid.org/0009-0000-7563-7370
Kujiraoka, Yuka
Okanami, Yuko https://orcid.org/0009-0008-2304-6518
Shinohara, Norimitsu https://orcid.org/0000-0002-0926-4235
Tsunoda, Hiroko https://orcid.org/0000-0002-6686-5133
Uematsu, Takayoshi https://orcid.org/0000-0003-4462-7430
Mukai, Hirofumi https://orcid.org/0000-0002-9292-5128
-
Clinical Trials BETA
Clinical trials referenced in this document:
umin000039009 at UMIN JapanDocuments that mention this clinical trial
Development of a deep learning-based automated diagnostic system (DLADS) for classifying mammographic lesions — a first large-scale multi-institutional clinical trial in Japan
https://doi.org/10.1007/s12282-025-01741-3
-
Funding
Funding for this research was provided by:
CSPOR-BC
- License Information
-
More Information
Article History
Received: 21 January 2025
Accepted: 18 June 2025
First Online: 3 July 2025
Declarations
:
: All authors declared no conflicts of interest.
: This trial was approved by the institutional review board of National Cancer Center Hospital East (Approval number: 2019–048). The need for signed informed consent was waived because of a retrospective study without patient interactions.
