AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue.

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AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue.

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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AutoIHC-scoring: a machine lea ...... -stained breast cancer tissue.

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P1476

AutoIHC-scoring: a machine lea ...... R-stained breast cancer tissue

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P2093

I Arun

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R Ahmed

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S Chatterjee

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S Tewary

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P2860

Thresholds for therapies: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2009

Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers

Quantitative image analysis of immunohistochemical stains using a CMYK color model.

Semi-automated imaging system to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer.

Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer.

Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer.

Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays.

Multiple immunoenzyme staining: methods and visualizations for the observation with spectral imaging.

Novel image analysis approach for quantifying expression of nuclear proteins assessed by immunohistochemistry: application to measurement of oestrogen and progesterone receptor levels in breast cancer.

Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts.

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172-185

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scholarly article

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10.1111/JMI.12596

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268

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C Chakraborty

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2017-06-14T00:00:00Z

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28613390

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automation

machine learning