论文标题
肺癌诊断，治疗和预后中的机器学习应用
Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis
论文作者
论文摘要
成像和测序技术的最新发展使肺癌临床研究的系统进步。同时，人的思想在有效地处理和充分利用了这种大量数据的积累方面受到限制。基于机器学习的方法在整合和分析这些大型且复杂的数据集中起着至关重要的作用，这些数据集通过使用这些应计数据的不同观点来广泛表征肺癌。在本文中，我们概述了基于机器学习的方法，以加强肺癌诊断和治疗的各个方面，包括早期发现，辅助诊断，预后预测和免疫疗法实践。此外，我们强调了机器学习在肺癌中未来应用的挑战和机会。
The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data. In this article, we provide an overview of machine learning-based approaches that strengthen the varying aspects of lung cancer diagnosis and therapy, including early detection, auxiliary diagnosis, prognosis prediction and immunotherapy practice. Moreover, we highlight the challenges and opportunities for future applications of machine learning in lung cancer.
