Artificial neural networks--a method for prediction of survival following liver resection for colorectal cancer metastases.
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Complementarity of Clinician Judgment and Evidence Based Models in Medical Decision Making: Antecedents, Prospects, and ChallengesPre-operative prediction of surgical morbidity in children: comparison of five statistical models.An Artificial Neural Network Stratifies the Risks of Reintervention and Mortality after Endovascular Aneurysm Repair; a Retrospective Observational studyA scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery.Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.The potential of interleukin 12 receptor beta 2 (IL12RB2) and tumor necrosis factor receptor superfamily member 8 (TNFRSF8) gene as diagnostic biomarkers of oral lichen planus (OLP).Comparison of Basic and Ensemble Data Mining Methods in Predicting 5-Year Survival of Colorectal Cancer Patients.Thymidylate synthase: a predictive biomarker in resected colorectal liver metastases receiving 5-FU treatment.
P2860
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P2860
Artificial neural networks--a method for prediction of survival following liver resection for colorectal cancer metastases.
description
2013 nî lūn-bûn
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2013年の論文
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2013年学术文章
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2013年学术文章
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2013年学术文章
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2013年学术文章
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2013年学术文章
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2013年學術文章
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name
Artificial neural networks--a ...... colorectal cancer metastases.
@en
Artificial neural networks--a ...... colorectal cancer metastases.
@nl
type
label
Artificial neural networks--a ...... colorectal cancer metastases.
@en
Artificial neural networks--a ...... colorectal cancer metastases.
@nl
prefLabel
Artificial neural networks--a ...... colorectal cancer metastases.
@en
Artificial neural networks--a ...... colorectal cancer metastases.
@nl
P2093
P1476
Artificial neural networks--a ...... r colorectal cancer metastases
@en
P2093
P304
P356
10.1016/J.EJSO.2013.02.024
P577
2013-03-17T00:00:00Z