Stratification of Breast Cancer in it's Preliminary Stages

V. Kiranmayee, Srishti Ranjan, J. Shreyansh, Shylesh Suresh, K. Ranjini
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引用次数: 1

Abstract

Classifying breast cancer in its preliminary stages is done with the help of machine learning and the concept of Transfer Learning Algorithm. Here, the classification is done by labeling the tumor as benign or malignant. The machine learning algorithms are implemented by using the scikit library in which transfer learning is also available. The algorithm completely depends upon the dataset that's run through it and the accuracy of the same. To get the best result, the usage of a pre-trained model approach will bolster the rate of accuracy. Once the algorithm is run, the desired result would be the algorithm predicting if the tumor is benign or malignant so the patient can get the most optimal care.
早期乳腺癌的分层研究
在早期阶段对乳腺癌进行分类是借助机器学习和迁移学习算法的概念完成的。在这里,分类是通过标记肿瘤为良性或恶性来完成的。机器学习算法是通过使用scikit库实现的,在scikit库中也可以使用迁移学习。该算法完全依赖于运行的数据集及其准确性。为了获得最佳结果,使用预训练的模型方法将提高准确率。一旦算法运行,期望的结果将是预测肿瘤是良性还是恶性的算法,这样患者就可以得到最优的治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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