Brain Tumor Analysis Empowered with Machine Learning and Deep Learning: A Comprehensive Review with its Recent Computational Techniques

Q2 Social Sciences
Dhaniya R.D., Dr. Umamaheswari K.M.
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引用次数: 0

Abstract

In driving the medical image research machine-learning and deep-learning algorithm are growing expeditiously. The premature conjecture of disease needs substantial attempts to diagnose the disease. The machine learning algorithm confesses the software application to study from the data and predicts more accurate outcome. The deep learning algorithm drives on extensive dataset imparts on high end machine and clarifies the problem end to end. The primary focus on the survey is to high-spots the machine and deep-learning approaches in medical image analysis that endorses the decision-making practices. The paper provides a plan for the researchers to perceive the extant schemes sustained out for medical imaging with its recognition and hindrances of the machine and deep learning algorithm.
利用机器学习和深度学习进行脑肿瘤分析:最新计算技术综述
在推动医学图像研究的过程中,机器学习和深度学习算法正在迅速发展。对疾病的过早推测需要大量的尝试来诊断疾病。机器学习算法承认软件应用程序可以从数据中学习并预测更准确的结果。深度学习算法在高端机器上驱动大量数据集,端到端地阐明问题。调查的主要重点是强调医学图像分析中的机器和深度学习方法,这些方法支持决策实践。本文为研究人员提供了一种方案来感知现有的医学成像方案,以及机器和深度学习算法的识别和障碍。
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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来源期刊
Webology
Webology Social Sciences-Library and Information Sciences
自引率
0.00%
发文量
374
审稿时长
10 weeks
期刊介绍: Webology is an international peer-reviewed journal in English devoted to the field of the World Wide Web and serves as a forum for discussion and experimentation. It serves as a forum for new research in information dissemination and communication processes in general, and in the context of the World Wide Web in particular. Concerns include the production, gathering, recording, processing, storing, representing, sharing, transmitting, retrieving, distribution, and dissemination of information, as well as its social and cultural impacts. There is a strong emphasis on the Web and new information technologies. Special topic issues are also often seen.
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