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Machine learning with textural analysis of longitudinal multiparametric MRI and molecular subtypes accurately predicts pathologic complete response in patients with invasive breast cancer.

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Title: Machine learning with textural analysis of longitudinal multiparametric MRI and molecular subtypes accurately predicts pathologic complete response in patients with invasive breast cancer.
Authors: Syed, Aaquib1 (AUTHOR), Adam, Richard1 (AUTHOR), Ren, Thomas1 (AUTHOR), Lu, Jinyu2 (AUTHOR), Maldjian, Takouhie1 (AUTHOR), Duong, Tim Q.1 (AUTHOR) Tim.duong@einsteinmed.org
Source: PLoS ONE. 1/17/2023, Vol. 18 Issue 1, p1-14. 14p.
Database: Academic Search Ultimate
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  Data: Machine learning with textural analysis of longitudinal multiparametric MRI and molecular subtypes accurately predicts pathologic complete response in patients with invasive breast cancer.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 1/17/2023, Vol. 18 Issue 1, p1-14. 14p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=161341792
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        Value: 10.1371/journal.pone.0280320
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        Text: English
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      – TitleFull: Machine learning with textural analysis of longitudinal multiparametric MRI and molecular subtypes accurately predicts pathologic complete response in patients with invasive breast cancer.
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              Text: 1/17/2023
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              Y: 2023
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