PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.

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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.

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2017 nî lūn-bûn

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2017年の論文

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2017年論文

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2017年論文

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2017年論文

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2017年論文

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2017年論文

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2017年论文

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2017年论文

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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.

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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.

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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.

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P1476

PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE

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P2093

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A Dekker

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Bgl Vanneste

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C Masciocchi

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E Meldolesi

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G C Mattiucci

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G Mantini

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P2860

Radiomics: extracting more information from medical images using advanced feature analysis

Radiomics: the process and the challenges

Missing data in medical databases: impute, delete or classify?

An umbrella protocol for standardized data collection (SDC) in rectal cancer: a prospective uniform naming and procedure convention to support personalized medicine.

Classification, predictive modelling, and statistical analysis of cancer data (a).

Standardized data collection to build prediction models in oncology: a prototype for rectal cancer.

Integration of prostate cancer clinical data using an ontology.

Rapid-learning system for cancer care.

Machine learning applications in cancer prognosis and prediction

Predicting outcomes in radiation oncology--multifactorial decision support systems

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2171-2181

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scholarly article

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10.2217/FON-2017-0142

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English

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2017-07-31T00:00:00Z

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28758431

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