Breast Cancer Predictions by Neural Networks Analysis: a Comparison with Logistic Regression

机译：神经网络分析对乳腺癌的预测：与逻辑回归的比较

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This paper presents an exploratory fixed time study to identify the most significant covariates as a precursor to a longitudinal study of specific mortality, disease free survival and disease recurrences. The data comprise consecutive patients diagnosed w

机译：本文提出了一项探索性固定时间研究，以将最重要的协变量确定为纵向研究特定死亡率，无病生存期和疾病复发的先兆。数据包括诊断为w的连续患者

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《Engineering in Medicine and Biology Society, 2007 Annual International Conference of the IEEE》|2007年|P.5424-5427|共4页
会议地点 Lyon,France
作者
Bourdes; V.S.; Bonnevay; S.; Lisboa; P.J.G.; Aung; M.S.H.; Chabaud; S.; Bachelot; T.; Perol; D.; Negrier; S.;
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biological organs; cancer; medical computing; multilayer perceptrons; regression analysis; sensitivity analysis; tumours; AUROC curves; Centre Leon Berard; French clinical center; Lyon; breast cancer prediction; disease free survival; disease recurrences; exploratory;

机译：生物器官癌症;医学计算；多层感知器回归分析;敏感性分析;肿瘤AUROC曲线中锋里昂·贝拉德；法国临床中心；里昂乳腺癌预测；无病生存；疾病复发；探索性的;

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1. Comparison of Artificial Neural Network with Logistic Regression as Classification Models for Variable Selection for Prediction of Breast Cancer Patient Outcomes [J] . ValérieBourdès, StéphaneBonnevay, PaoloLisboa, Advances in artificial neural systems . 2010,第1期

机译：人工神经网络与Logistic回归作为预测乳腺癌患者结果的变量选择分类模型的比较
2. Comparison of the Performance of Log-logistic Regression and Artificial Neural Networks for Predicting Breast Cancer Relapse [J] . Javad Faradmal, Ali Reza Soltanian, Ghodratollah Roshanaei, Asian Pacific Journal of Cancer Prevention . 2014,第14期

机译：对数逻辑回归和人工神经网络预测乳腺癌复发性能的比较
3. Comparison of Logistic Regression and Bayesian Networks for Risk Prediction of Breast Cancer Recurrence [J] . Witteveen Annemieke, Nane Gabriela F., Vliegen Ingrid M. H., Medical decision making: An international journal of the Society for Medical Decision Making . 2018,第7期

机译：乳腺癌复发风险预测逻辑回归与贝叶斯网络的比较
4. Breast Cancer Predictions by Neural Networks Analysis: a Comparison with Logistic Regression [C] . Bourdes V.S., Bonnevay S., Lisboa P. J.G., Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2007

机译：神经网络分析的乳腺癌预测：与Logistic回归的比较
5. Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures. [D] . Parsons, Thomas D. 2004

机译：乳腺癌研究的统计模式识别：理论驱动的一般线性模型方法与数据驱动的人工神经网络体系结构的比较。
6. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy sensitivity and specificity of linear discriminant analysis logistic regression neural networks support vector machines classification trees and random forests [O] . João Maroco, Dina Silva, Ana Rodrigues, 2011

机译：痴呆症预测中的数据挖掘方法：线性判别分析逻辑回归神经网络支持向量机分类树和随机森林的准确性敏感性和特异性的真实数据比较
7. Comparison of the Performance of Log-logistic Regression and Artificial Neural Networks for Predicting Breast Cancer Relapse [O] . Javad Faradmal, Ali Reza Soltanian, Ghodratollah Roshanaei, 2014

机译：对数逻辑回归和人工神经网络预测乳腺癌复发性能的比较
8. Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors. [R] . Ottati, A. 2015

机译：神经网络和线性回归模型在统计预测乳腺癌幸存者心理和身体健康状况中的比较。

Breast Cancer Predictions by Neural Networks Analysis: a Comparison with Logistic Regression

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