Supervised and Unsupervised Machine Learning for Cancer Classification: Recent Development

Aina Umairah Mazlan, N. A. Sahabudin, Muhammad Akmal bin Remli, N. N. Ismail, M. S. Mohamad, Nor Bakiah Abd Warif
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引用次数: 1

Abstract

This is models with the ability to detect and classify cancer is important in the industrial of healthcare. The most difficult aspect for such model is the classification of cancer, which can be addressed using machine learning methods. The methods are used to improve classification accuracy between system output and test data. The classification process becomes more difficult due to vast data information. This paper presents an overview on current development of cancer classification techniques using machine learning methods, which have received increasing attention within the area of healthcare. This review will mainly focus on the development of machine learning methods for classification of cancer diseases. Recently, there are various researchers proposed different kinds of methods for cancer classification. The results show that the successful of cancer classification is dependent on the machine learning models. Besides, various types of healthcare data used in the experiments would also be discussed in this paper. The development of many optimization methods for cancer classification has brought a lot of improvement in the healthcare field. There is demand for further improvements in optimization methods to develop better machine learning models for cancer classification.
癌症分类的监督和非监督机器学习:最新进展
这种具有检测和分类癌症能力的模型在医疗保健行业非常重要。这种模型最困难的方面是癌症的分类,这可以使用机器学习方法来解决。该方法用于提高系统输出和测试数据之间的分类精度。由于海量的数据信息,分类过程变得更加困难。本文概述了目前使用机器学习方法的癌症分类技术的发展,这些技术在医疗保健领域受到越来越多的关注。本文将主要介绍机器学习方法在癌症疾病分类方面的发展。近年来,不同的研究者提出了不同的癌症分类方法。结果表明,癌症分类的成功依赖于机器学习模型。此外,本文还将讨论实验中使用的各种医疗保健数据。许多癌症分类优化方法的发展给医疗保健领域带来了很大的改善。需要进一步改进优化方法,以开发更好的癌症分类机器学习模型。
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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