Lung cancer is the leading cause of death among different types of cancers. Every year, the lives lost due to lung cancer exceed those lost to pancreatic, breast, and prostate cancer combined. The survival rate for lung cancer patients is very low compared to other cancer patients due to late diagnostics. Thus, early lung cancer diagnostics is crucial for patients to receive early treatments, increasing the survival rate or even becoming cancer-free. This paper proposed a deep-learning model for early lung cancer prediction and diagnosis from Computed Tomography (CT) scans. The proposed mode achieves high accuracy. In addition, it can be a beneficial tool to support radiologists' decisions in predicting and detecting lung cancer and its stage.
翻译:肺癌是不同类型癌症死亡的主要原因。每年,肺癌造成的死亡总和超过胰腺癌、乳腺癌和前列腺癌造成的死亡。与其他癌症患者相比,肺癌患者由于晚期诊断而存活率非常低。因此,早期肺癌诊断对于患者获得早期治疗、提高存活率甚至成为无癌症患者至关重要。本文提出了一个深层学习模式,用于对肺癌进行早期预测和诊断。拟议模式的准确性很高。此外,它可以成为支持放射学家预测和检测肺癌及其阶段的决定的有益工具。