Applying a new quantitative global breast MRI feature analysis scheme to assess tumor response to chemotherapy.
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Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome.Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.Computer-aided classification of mammographic masses using visually sensitive image features.Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy.
P2860
Applying a new quantitative global breast MRI feature analysis scheme to assess tumor response to chemotherapy.
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2016 nî lūn-bûn
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2016年の論文
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2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
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2016年論文
@zh-tw
2016年论文
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2016年论文
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2016年论文
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name
Applying a new quantitative gl ...... umor response to chemotherapy.
@en
Applying a new quantitative gl ...... umor response to chemotherapy.
@nl
type
label
Applying a new quantitative gl ...... umor response to chemotherapy.
@en
Applying a new quantitative gl ...... umor response to chemotherapy.
@nl
prefLabel
Applying a new quantitative gl ...... umor response to chemotherapy.
@en
Applying a new quantitative gl ...... umor response to chemotherapy.
@nl
P2093
P2860
P356
P1476
Applying a new quantitative gl ...... umor response to chemotherapy.
@en
P2093
Alan B Hollingsworth
Faranak Aghaei
Maxine Tan
P2860
P304
P356
10.1002/JMRI.25276
P577
2016-04-15T00:00:00Z