Harnessing transformers: A leap forward in lung cancer image detection

A Bechar, Y Elmir, R Medjoudj… - 2023 6th International …, 2023 - ieeexplore.ieee.org
This paper discusses the role of Transfer Learning (TL) and transformers in cancer detection
based on image analysis. With the enormous evolution of cancer patients, the identification …

Comparing CNN-based and transformer-based models for identifying lung cancer: which is more effective?

L Gai, M Xing, W Chen, Y Zhang, X Qiao - Multimedia Tools and …, 2023 - Springer
Lung cancer constitutes the most severe cause of cancer-related mortality. Recent evidence
supports that early detection by means of computed tomography (CT) scans significantly …

A Transfer Learning for Intelligent Prediction of Lung Cancer Detection

TT Al-Shouka, KMA Alheeti - 2023 Al-Sadiq International …, 2023 - ieeexplore.ieee.org
Cancer is a widespread and potentially lethal illness. There are many different types of
cancer. The most common type of cancer is lung cancer. High mortality rates from lung …

The impact of transfer learning on lung cancer detection using various deep neural network architectures

N Vijayan, J Kuruvilla - 2022 IEEE 19th India Council …, 2022 - ieeexplore.ieee.org
Lung cancer is the primary reason for death among cancer patients. Early diagnosis of lung
cancer in patients has a much higher chance of survival than when lung cancer has spread …

Transfer learning for histopathology images: an empirical study

T Aitazaz, A Tubaishat, F Al-Obeidat, B Shah… - Neural Computing and …, 2023 - Springer
Histopathology imaging is one of the key methods used to determine the presence of
cancerous cells. However, determining the results from such medical images is a tedious …

Lung cancer CT image classification using hybrid-SVM transfer learning approach

S Nigudgi, C Bhyri - Soft Computing, 2023 - Springer
Lung cancer is a leading deadly form of the illness that is the cause of one million deaths
around the world every year. Identification of lung nodules on chest computed tomography …

BiCFormer: Swin Transformer based model for classification of benign and malignant pulmonary nodules

X Zhao, J Xu, Z Lin, X Xue - Measurement Science and …, 2024 - iopscience.iop.org
Pulmonary cancer is one of the most common and deadliest cancers worldwide, and the
detection of benign and malignant nodules in the lungs can be an important aid in the early …

A transformer‐based deep neural network for detection and classification of lung cancer via PET/CT images

K Barbouchi, D El Hamdi, I Elouedi… - … Journal of Imaging …, 2023 - Wiley Online Library
Lung cancer is the leading cause of death for men and women worldwide and the second
most frequent cancer. Therefore, early detection of the disease increases the cure rate. This …

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 …

[PDF][PDF] Application of transfer learning technique for detection and classification of lung cancer using CT images

A Mohite - Int J Sci Res Manag, 2021 - researchgate.net
Lung cancer is unquestionably a lung-influencing chronic condition that significantly
hampers the respiratory system. It is the second most dangerous disease which causes …