Probability of malignancy for lesions detected on breast MRI: a predictive model incorporating BI-RADS imaging features and patient characteristics.

Probability of malignancy for lesions detected on breast MRI: a predictive model incorporating BI-RADS imaging features and patient characteristics.

Item
http://www.wikidata.org/entity/Q37848173
Improved T1, contrast concentration, and pharmacokinetic parameter quantification in the presence of fat with two-point Dixon for dynamic contrast-enhanced magnetic resonance imaging.Breast DCE-MRI: influence of postcontrast timing on automated lesion kinetics assessments and discrimination of benign and malignant lesions.Utility of targeted sonography in management of probably benign breast lesions identified on magnetic resonance imaging.A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.MRI-guided breast needle core biopsies: pathologic features of newly diagnosed malignancies.Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial.Computer-aided diagnosis for dynamic contrast-enhanced breast MRI of mass-like lesions using a multiparametric model combining a selection of morphological, kinetic, and spatiotemporal features.
P2860

Probability of malignancy for lesions detected on breast MRI: a predictive model incorporating BI-RADS imaging features and patient characteristics.

Item
http://www.wikidata.org/entity/Q37848173
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 27 February 2011
@en
vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
Probability of malignancy for ...... s and patient characteristics.
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Probability of malignancy for ...... s and patient characteristics.
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Probability of malignancy for ...... s and patient characteristics.
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Probability of malignancy for ...... s and patient characteristics.
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Probability of malignancy for ...... s and patient characteristics.
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Probability of malignancy for ...... es and patient characteristics
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