APPLICATION OF DEEP LEARNING MODELS IN LUNG CANCER DIAGNOSIS
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Abstract
Nowadays, with the development of modern medicine, lung cancer patients are increasingly detected early. However, only about 30% of these patients are able to undergo surgery for better treatment. Some types of lung cancer are determined by the type of cells that can be detected under a microscope, which are about 85% of non-small cell lung cancer cases and the rest are small cell lung cancer. The study proposes an improvement of the Unet model to detect and diagnose lung cancer based on the IQ-OTH/NCCD dataset, which gives better results than other deep learning methods such as VGG-16, ResNet-50, NasNet Mobile, ViT.
Keywords: deep learning method, lung cancer diagnosis, Unet model.