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Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients.

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Title: Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients.
Authors: Dodington DW; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada., Lagree A; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada., Tabbarah S; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada., Mohebpour M; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada., Sadeghi-Naini A; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.; Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada., Tran WT; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.; Temerty Centre for Artificial Intelligence Research and Education in Medicine, University of Toronto, Toronto, ON, Canada., Lu FI; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. fangi.lu@sunnybrook.ca.; Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, 2075 Bayview Ave., Rm E423a, Toronto, ON, M4N 3M5, Canada. fangi.lu@sunnybrook.ca.
Source: Breast cancer research and treatment [Breast Cancer Res Treat] 2021 Apr; Vol. 186 (2), pp. 379-389. Date of Electronic Publication: 2021 Jan 23.
Publication Type: Journal Article
Journal Info: Publisher: Kluwer Academic Country of Publication: Netherlands NLM ID: 8111104 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-7217 (Electronic) Linking ISSN: 01676806 NLM ISO Abbreviation: Breast Cancer Res Treat Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients.
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  Data: <searchLink fieldCode="AU" term="%22Dodington+DW%22">Dodington DW</searchLink>; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Lagree+A%22">Lagree A</searchLink>; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Tabbarah+S%22">Tabbarah S</searchLink>; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Mohebpour+M%22">Mohebpour M</searchLink>; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Sadeghi-Naini+A%22">Sadeghi-Naini A</searchLink>; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.; Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Tran+WT%22">Tran WT</searchLink>; Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.; Temerty Centre for Artificial Intelligence Research and Education in Medicine, University of Toronto, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Lu+FI%22">Lu FI</searchLink>; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. fangi.lu@sunnybrook.ca.; Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, 2075 Bayview Ave., Rm E423a, Toronto, ON, M4N 3M5, Canada. fangi.lu@sunnybrook.ca.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Kluwer+Academic%22">Kluwer Academic </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>8111104 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1573-7217 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2201676806%22">01676806 </searchLink><i>NLM ISO Abbreviation: </i>Breast Cancer Res Treat <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s10549-020-06093-4
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        Text: English
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      – TitleFull: Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients.
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              Text: 2021 Apr
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