Multiround transfer learning and modified generative adversarial network for lung cancer detection
KT Chui, BB Gupta, RH Jhaveri, HR Chi… - … Journal of Intelligent …, 2023 - Wiley Online Library
Lung cancer has been the leading cause of cancer death for many decades. With the advent
of artificial intelligence, various machine learning models have been proposed for lung …
of artificial intelligence, various machine learning models have been proposed for lung …
LCDAE: data augmented ensemble framework for lung cancer classification
Objective: The only possible solution to increase the patients' fatality rate is lung cancer
early-stage detection. Recently, deep learning techniques became the most promising …
early-stage detection. Recently, deep learning techniques became the most promising …
Unsupervised multi-discriminator generative adversarial network for lung nodule malignancy classification
Computer-aided diagnosis systems with deep learning frameworks have been used to
identify benign and malignant pulmonary nodules in lung cancer diagnosis. It's commonly …
identify benign and malignant pulmonary nodules in lung cancer diagnosis. It's commonly …
A hybrid framework for lung cancer classification
Cancer is the second leading cause of death worldwide, and the death rate of lung cancer is
much higher than other types of cancers. In recent years, numerous novel computer-aided …
much higher than other types of cancers. In recent years, numerous novel computer-aided …
Classification of pathological types of lung cancer from CT images by deep residual neural networks with transfer learning strategy
S Wang, L Dong, X Wang, X Wang - Open Medicine, 2020 - degruyter.com
Lung cancer is one of the most harmful malignant tumors to human health. The accurate
judgment of the pathological type of lung cancer is vital for treatment. Traditionally, the …
judgment of the pathological type of lung cancer is vital for treatment. Traditionally, the …
Lung nodule malignancy classification in chest computed tomography images using transfer learning and convolutional neural networks
RVM Da Nobrega, PP Reboucas Filho… - Neural Computing and …, 2020 - Springer
Lung cancer accounts for more than 1.5 million deaths worldwide, and it corresponded to
26% of all deaths due to cancer in 2017. However, lung computer-aided diagnosis systems …
26% of all deaths due to cancer in 2017. However, lung computer-aided diagnosis systems …
A transfer learning approach with a convolutional neural network for the classification of lung carcinoma
Lung cancer is among the most hazardous types of cancer in humans. The correct diagnosis
of pathogenic lung disease is critical for medication. Traditionally, determining the …
of pathogenic lung disease is critical for medication. Traditionally, determining the …
Ensemble transfer learning for lung cancer detection
M Phankokkruad - 2021 4th international conference on data science …, 2021 - dl.acm.org
Lung cancer is the most leading cause of death. One of the significant screening problems is
the difficulty in diagnosing it at an early stage. Consequently, this is a better way to study the …
the difficulty in diagnosing it at an early stage. Consequently, this is a better way to study the …
Automatic prognosis of lung cancer using heterogeneous deep learning models for nodule detection and eliciting its morphological features
W Wang, G Charkborty - Applied Intelligence, 2021 - Springer
Among cancers, lung cancer has the highest morbidity, and mortality rate. The survival
probability of lung cancer patients depends largely on an early diagnosis. For predicting …
probability of lung cancer patients depends largely on an early diagnosis. For predicting …
[Retracted] Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator
Cancer is a complicated worldwide health issue with an increasing death rate in recent
years. With the swift blooming of the high throughput technology and several machine …
years. With the swift blooming of the high throughput technology and several machine …