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Refinado por: Nome da Publicação: Clinical Radiology remover
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Artificial intelligence in breast imaging
Artificial intelligence in breast imaging
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Artificial intelligence in breast imaging

Le, E.P.V. ; Wang, Y. ; Huang, Y. ; Hickman, S. ; Gilbert, F.J.

Clinical radiology, 2019-05, Vol.74 (5), p.357-366 [Periódico revisado por pares]

England: Elsevier Ltd

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Digital tomosynthesis: A new future for breast imaging?
Digital tomosynthesis: A new future for breast imaging?
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Digital tomosynthesis: A new future for breast imaging?

Alakhras, M ; Bourne, R ; Rickard, M ; Ng, K.H ; Pietrzyk, M ; Brennan, P.C

Clinical radiology, 2013-05, Vol.68 (5), p.e225-e236 [Periódico revisado por pares]

England: Elsevier Ltd

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3
Interobserver variability in upgraded and non-upgraded BI-RADS 3 lesions
Interobserver variability in upgraded and non-upgraded BI-RADS 3 lesions
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Interobserver variability in upgraded and non-upgraded BI-RADS 3 lesions

Michaels, A.Y ; Chung, C.S.W ; Frost, E.P ; Birdwell, R.L ; Giess, C.S

Clinical radiology, 2017-08, Vol.72 (8), p.694.e1-694.e6 [Periódico revisado por pares]

England: Elsevier Ltd

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4
Role of performance metrics in breast screening imaging – where are we and where should we be?
Role of performance metrics in breast screening imaging – where are we and where should we be?
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Role of performance metrics in breast screening imaging – where are we and where should we be?

Cohen, S.L. ; Blanks, R.G. ; Jenkins, J. ; Kearins, O.

Clinical radiology, 2018-04, Vol.73 (4), p.381-388 [Periódico revisado por pares]

England: Elsevier Ltd

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5
Could parenchymal enhancement on contrast-enhanced spectral mammography (CESM) represent a new breast cancer risk factor? Correlation with known radiology risk factors
Could parenchymal enhancement on contrast-enhanced spectral mammography (CESM) represent a new breast cancer risk factor? Correlation with known radiology risk factors
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Could parenchymal enhancement on contrast-enhanced spectral mammography (CESM) represent a new breast cancer risk factor? Correlation with known radiology risk factors

Savaridas, S.L. ; Taylor, D.B. ; Gunawardana, D. ; Phillips, M.

Clinical radiology, 2017-12, Vol.72 (12), p.1085.e1-1085.e9 [Periódico revisado por pares]

England: Elsevier Ltd

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6
Radiological characteristics of invasive micropapillary carcinoma of the breast
Radiological characteristics of invasive micropapillary carcinoma of the breast
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Radiological characteristics of invasive micropapillary carcinoma of the breast

Fakhry, S. ; Ali Ibrahim Nada, Y. Mohamed ; Mohamed, M. Metawee ; Kamal, R. Mohamed ; Eltohamy, M. Ibrahim ; Mohamed Taha, S. Nasser ; Mustafa Sweed, E. Mohamed

Clinical radiology, 2024-01, Vol.79 (1), p.e34-e40 [Periódico revisado por pares]

England: Elsevier Ltd

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7
Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool
Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool
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Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool

Gilbert, Fiona J ; Tucker, Lorraine ; Young, Ken C

Clinical radiology, 2016-02, Vol.71 (2), p.141-150 [Periódico revisado por pares]

England: Elsevier Ltd

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8
Quantifying lesion enhancement on contrast-enhanced mammography: a review of published data
Quantifying lesion enhancement on contrast-enhanced mammography: a review of published data
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Quantifying lesion enhancement on contrast-enhanced mammography: a review of published data

Savaridas, S.L. ; Tennant, S.L.

Clinical radiology, 2022-04, Vol.77 (4), p.e313-e320 [Periódico revisado por pares]

England: Elsevier Ltd

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9
Test-set training improves the detection rates of invasive cancer in screening mammography
Test-set training improves the detection rates of invasive cancer in screening mammography
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Test-set training improves the detection rates of invasive cancer in screening mammography

Qenam, B.A. ; Li, T. ; Ekpo, E. ; Frazer, H. ; Brennan, P.C.

Clinical radiology, 2023-03, Vol.78 (3), p.e260-e267 [Periódico revisado por pares]

England: Elsevier Ltd

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10
The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country
The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country
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The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country

Çelik, L. ; Aribal, E.

Clinical radiology, 2024-07, Vol.79 (7), p.e885-e891 [Periódico revisado por pares]

England: Elsevier Ltd

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