Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence.

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Bibliographic Details
Title: Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence.
Authors: Kai C; Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan.; Major in Health and Welfare, Graduate School of Niigata University of Health and Welfare, Niigata, Niigata, Japan., Otsuka T; Otsuka Breastcare Clinic, Tokyo, Japan., Nara M; Department of Breast Surgery, Tokyo Metropolitan Cancer and Infectious Disease Center, Komagome Hospital, Tokyo, Japan., Kondo S; Graduate School of Engineering, Muroran Institute of Technology, Muroran, Hokkaido, Japan., Futamura H; Healthcare Business Headquarters, Konica Minolta, Inc., Tokyo, Japan., Kodama N; Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan., Kasai S; Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan.
Source: Frontiers in oncology [Front Oncol] 2024 Mar 05; Vol. 14, pp. 1255109. Date of Electronic Publication: 2024 Mar 05 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2234-943X
DOI:10.3389/fonc.2024.1255109