人工智能技术在癌症检测中的应用

Darshan Patel, Yash Shah, Nisarg Thakkar, Kush Shah, Manan Shah
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引用次数: 51

摘要

像癌症这样的疾病由于其致命性而被称为慢性致命疾病。癌症之所以被称为致命,是因为癌症进展更快,而且在大多数情况下,这些细胞是在晚期检测到的。发现早期发现癌症是降低死亡率的关键。本研究综述了人工智能技术在乳腺癌、肺癌和肝癌三种癌症诊断中的应用。综述了用于癌症早期检测的不同类型的系统的各种研究。具有人工智能的自动化或计算机辅助系统被认为是完美的,因为它们提供了处理大型数据集的精确性和效率,可以检测癌症。诊断和治疗可以在这些系统的帮助下进行。乳腺癌、肺癌和肝癌癌症研究表明,其中一些系统在诊断中提供了准确的精度,因此如果实施这些系统,可以解决问题。然而,这些系统要大规模实施,必须面临许多障碍。图像预处理、数据管理等技术也需要增强,才能与人工智能和机器学习算法兼容。考虑到实验结果,本研究表明,AI实现的神经网络无疑将是癌症诊断和治疗的未来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Artificial Intelligence Techniques for Cancer Detection

Diseases like cancer have been termed as chronic fatal disease because of its deadly nature. The reason why cancer is termed as fatal is cancer progresses faster, and in most of the cases, these cells are detected at an advance stage. It is found that early detection of cancer is the key to lower death rate. In this study, overviews of applying AI technology for diagnosis of three types of cancer, breast, lung and liver, have been demonstrated. Various studies are reviewed for the different types of systems which are used for early detection of cancer. Automated or computer-aided systems with AI are considered as they provide a perfect fit to process a large dataset with accuracy and efficiency in detecting cancer. Diagnosis and treatment can be carried out with the help of these systems. Breast, lung and liver cancer studies have shown that some of these systems provide accurate precision in diagnosis and thus can solve the problem if these systems are implemented. However, these systems have to face a lot of hurdles to be implemented on a large scale. Image preprocessing, data management and other technology also need enhancement to be compatible with AI and machine learning algorithms to be implemented. Considering the experimental results, this study shows there is no doubt that the AI-implemented neural networks would be the future in cancer diagnosis and treatment.

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