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Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.

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Title: Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.
Authors: Kim H; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Choi JS; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. jisoo.choi@samsung.com.; Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea. jisoo.choi@samsung.com., Chi SA; Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea., Ryu JM; Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Lee JE; Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Kim MK; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Lee J; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Ko ES; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Ko EY; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea., Han BK; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Source: European radiology [Eur Radiol] 2025 Sep; Vol. 35 (9), pp. 5671-5684. Date of Electronic Publication: 2025 Mar 25.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.
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  Data: <searchLink fieldCode="AU" term="%22Kim+H%22">Kim H</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Choi+JS%22">Choi JS</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. jisoo.choi@samsung.com.; Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea. jisoo.choi@samsung.com.<br /><searchLink fieldCode="AU" term="%22Chi+SA%22">Chi SA</searchLink>; Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Ryu+JM%22">Ryu JM</searchLink>; Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Lee+JE%22">Lee JE</searchLink>; Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+MK%22">Kim MK</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Lee+J%22">Lee J</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Ko+ES%22">Ko ES</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Ko+EY%22">Ko EY</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Han+BK%22">Han BK</searchLink>; Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
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  Data: <searchLink fieldCode="JN" term="%229114774%22">European radiology</searchLink> [Eur Radiol] 2025 Sep; Vol. 35 (9), pp. 5671-5684. <i>Date of Electronic Publication: </i>2025 Mar 25.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+International%22">Springer International </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>9114774 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1432-1084 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209387994%22">09387994 </searchLink><i>NLM ISO Abbreviation: </i>Eur Radiol <i>Subsets: </i>MEDLINE
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              M: 09
              Text: 2025 Sep
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