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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| Title: | 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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| 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 38505584 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Kai+C%22">Kai C</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Otsuka+T%22">Otsuka T</searchLink>; Otsuka Breastcare Clinic, Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Nara+M%22">Nara M</searchLink>; Department of Breast Surgery, Tokyo Metropolitan Cancer and Infectious Disease Center, Komagome Hospital, Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Kondo+S%22">Kondo S</searchLink>; Graduate School of Engineering, Muroran Institute of Technology, Muroran, Hokkaido, Japan.<br /><searchLink fieldCode="AU" term="%22Futamura+H%22">Futamura H</searchLink>; Healthcare Business Headquarters, Konica Minolta, Inc., Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Kodama+N%22">Kodama N</searchLink>; Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan.<br /><searchLink fieldCode="AU" term="%22Kasai+S%22">Kasai S</searchLink>; Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101568867%22">Frontiers in oncology</searchLink> [Front Oncol] 2024 Mar 05; Vol. 14, pp. 1255109. <i>Date of Electronic Publication: </i>2024 Mar 05 (<i>Print Publication: </i>2024). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Research+Foundation]%22">Frontiers Research Foundation] </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101568867 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2234-943X (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222234943X%22">2234943X </searchLink><i>NLM ISO Abbreviation: </i>Front Oncol <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=38505584 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fonc.2024.1255109 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 1255109 Titles: – TitleFull: Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kai C – PersonEntity: Name: NameFull: Otsuka T – PersonEntity: Name: NameFull: Nara M – PersonEntity: Name: NameFull: Kondo S – PersonEntity: Name: NameFull: Futamura H – PersonEntity: Name: NameFull: Kodama N – PersonEntity: Name: NameFull: Kasai S IsPartOfRelationships: – BibEntity: Dates: – D: 05 M: 03 Text: 2024 Mar 05 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 2234-943X Numbering: – Type: volume Value: 14 Titles: – TitleFull: Frontiers in oncology Type: main |
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