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Hybrid intelligent systems in survival prediction of breast cancer

机译:乳腺癌存活预测中的杂交智能系统

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Hybrid intelligent systems play an important role in the survival prediction of breast cancer. The life-expectancy prediction of a patient is highly significant in decision making for treatments, medications and therapies. This paper addresses the motivation behind the need of hybrid model approach to survival prediction for breast cancer. The conventional approach of survival prediction faces difficulties in handling complex non-linear correlation between the prognostic factors and tumor progression, the censoring issue in medical data and the need to process the growing number of macro-scale and molecular-scale prognostic factors. The issues in breast cancer survivability are discussed with some examples of prominent works from machine learning approaches. Current trends and advancements of hybrid intelligent system are also presented.
机译:杂交智能系统在乳腺癌的生存预测中发挥着重要作用。在治疗,药物和治疗的决策中,患者的预期预期预测非常重要。本文解决了杂交模型方法对乳腺癌生存预测的需要背后的动力。生存预测的常规方法面临处理预后因子和肿瘤进展之间的复杂非线性相关性,医疗数据的审查问题以及处理越来越多的宏观规模和分子规范预后因素的审查问题。乳腺癌生存能力的问题与机器学习方法的一些突出作品的例子讨论过。还提出了混合智能系统的当前趋势和进步。

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