A systematic review of modern approaches in healthcare systems for lung cancer detection and classification
SK Pandey, AK Bhandari - Archives of Computational Methods in …, 2023 - Springer
Lung cancer has become a prevalent form of cancer; it can be found in persons of all age
groups. The early stage identification of lung cancer is required to control the integrated …
groups. The early stage identification of lung cancer is required to control the integrated …
A novel lightweight lung cancer classifier through hybridization of DNN and comparative feature optimizer
The likelihood of successful early cancer nodule detection rises from 68% to 82% when a
second radiologist aids in diagnosing lung cancer. Lung cancer nodules can be accurately …
second radiologist aids in diagnosing lung cancer. Lung cancer nodules can be accurately …
Deep learning-based lung cancer detection using convolutional neural networks
S Khattar, M Aftaab, T Verma, D Patial, B Kaur… - AIP Conference …, 2024 - pubs.aip.org
Lung cancer is one of the most prevalent cancers in the world and is responsible for most
cancer-related fatalities. The present methods for identifying lung cancer, such as CT scans …
cancer-related fatalities. The present methods for identifying lung cancer, such as CT scans …
Enhancing Lung Cancer Diagnosis with MATLAB and GLCM: A Robust Image Processing Approach
A Palit, K Ganguly, M Mukherjee - TWIST, 2024 - twistjournal.net
This study presents a novel approach to the diagnosis of lung cancer by utilizing MATLAB to
integrate modern image processing. Our method simplifies recognizing malignant phases by …
integrate modern image processing. Our method simplifies recognizing malignant phases by …