癌症研究中的人工智能技术:机遇与挑战

Surbhi Gupta, Anish Gupta, Yogesh Kumar
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引用次数: 4

摘要

在全球范围内,癌症是导致死亡和发病的主要原因。在过去的三十年里,随着自动学习技术的出现,癌症研究逐渐得到了改善。人工智能(AI)实践已经成为预测建模的宝贵工具。基于人工智能的预测模型可以作为临床决策支持系统,并有助于提高癌症死亡率。在癌症的早期阶段进行了杰出的研究工作。从机器学习到深度学习架构的人工智能实践已被用于癌症预测。尽管在临床环境中缺乏对人工智能预测模型的验证,但许多研究仍然取得了比医生更好的预测结果,他们主张将人工智能整合到现实环境中。这篇综述文章旨在强调人工智能在癌症检测方面的潜力。本研究还概述了用于癌症诊断的自动预测框架。
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Artificial intelligence techniques in Cancer research: Opportunities and challenges
Cancer is a leading cause of mortality and morbidity on a global scale. Cancer research has gradually improved in the past three decades with the advent of automated learning techniques. Artificial Intelligence (AI) practices have emerged as valuable tools in predictive modeling. AI-based prediction models can serve as clinical decision support systems and aid in improving cancer mortality rates. Prominent research works have been conducted to predict cancer at an early stage. AI practices extending from machine learning to deep learning architectures have been employed in cancer prediction. Although the validation of AI prediction models in clinical settings is missing, many studies have still achieved better prediction outcomes than physicians, which advocate integrating AI in real-world settings. The review paper aims to highlight the potential of AI in cancer detection. This study also provides an outline of the automated prediction framework used for the diagnosis of cancer.
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