Pancreatic Cancer Detection using Machine and Deep Learning Techniques

Anish Gupta, Apeksha Koul, Yogesh Kumar
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引用次数: 9

Abstract

Despite substantial research, pancreatic cancer has a terrible prognosis by having a survival rate of five years only. The premise behind early detection and better survival is that more people will benefit from a possible treatment. In general health care, machine and deep learning algorithms have shown to be a viable tool to classify or detect the risk of pancreatic cancer. As a result, in this work, we looked into various researchers' methods for diagnosing pancreatic cancer using machine and deep learning models. In addition, the report highlighted their achievements and the obstacles that remain in this sector. We incorporated our evaluation of the numerous strategies available to make some conclusions.
使用机器和深度学习技术进行胰腺癌检测
尽管有大量的研究,胰腺癌的预后很糟糕,生存率只有5年。早期发现和更好的生存率背后的前提是更多的人将从可能的治疗中受益。在一般医疗保健中,机器和深度学习算法已被证明是分类或检测胰腺癌风险的可行工具。因此,在这项工作中,我们研究了各种研究人员使用机器和深度学习模型诊断胰腺癌的方法。此外,报告强调了它们的成就和在这一部门仍然存在的障碍。我们综合了对众多可用策略的评估,得出了一些结论。
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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