Lung cancer detection from CT scans using modified DenseNet with feature selection methods and ML classifiers
MG Lanjewar, KG Panchbhai, P Charanarur - Expert Systems with …, 2023 - Elsevier
Lung cancer is a highly life-threatening disease worldwide, and detection is crucial. In this
study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four …
study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four …
LCD-capsule network for the detection and classification of lung cancer on computed tomography images
Lung cancer is the second most prominent cancer in men and women, and it is also the
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
Dynamic learning for imbalanced data in learning chest X-ray and CT images
Massive annotated datasets are necessary for networks of deep learning. When a topic is
being researched for the first time, as in the situation of the viral epidemic, handling it with …
being researched for the first time, as in the situation of the viral epidemic, handling it with …
MENet: A Mitscherlich function based ensemble of CNN models to classify lung cancer using CT scans
Lung cancer is one of the leading causes of cancer-related deaths worldwide. To reduce the
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
Comprehensive review of reinforcement learning in lung cancer diagnosis and treatment: Taxonomy, challenges and recommendations
M Ghorbian, S Ghorbian - Computers in Biology and Medicine, 2024 - Elsevier
Lung cancer (LuC) is one of the leading causes of death in the world, and due to the
complex mechanisms and widespread metastasis, diagnosis and treatment are challenging …
complex mechanisms and widespread metastasis, diagnosis and treatment are challenging …
Lung cancer detection and classification using deep neural network based on hybrid metaheuristic algorithm
U Prasad, S Chakravarty, G Mahto - Soft Computing, 2024 - Springer
Lung cancer causes millions of deaths annually, and CT scans and lung X-rays are common
diagnostic tools. However, large datasets can contain noisy and irrelevant features that can …
diagnostic tools. However, large datasets can contain noisy and irrelevant features that can …
An efficient lung cancer detection using optimal SVM and improved weight based beetle swarm optimization
N Venkatesan, S Pasupathy, B Gobinathan - Biomedical Signal Processing …, 2024 - Elsevier
Lung cancer is caused by uncontrolled cell growth in the lung tissue. Early detection of lung
cancer is important for correct detection and availability of treatment. Diagnosing lung …
cancer is important for correct detection and availability of treatment. Diagnosing lung …
Computer-aided diagnosis for lung cancer using waterwheel plant algorithm with deep learning
Lung cancer (LC) is a life-threatening and dangerous disease all over the world. However,
earlier diagnoses and treatment can save lives. Earlier diagnoses of malevolent cells in the …
earlier diagnoses and treatment can save lives. Earlier diagnoses of malevolent cells in the …
Lung cancer detection from thoracic CT scans using an ensemble of deep learning models
Lung cancer remains a prevalent and deadly disease, claiming numerous lives annually.
Early detection plays a pivotal role in significantly improving survival rates, by up to 50–70 …
Early detection plays a pivotal role in significantly improving survival rates, by up to 50–70 …
Advancing breast ultrasound diagnostics through hybrid deep learning models
Today, doctors rely heavily on medical imaging to identify abnormalities. Proper
classification of these abnormalities enables them to take informed actions, leading to early …
classification of these abnormalities enables them to take informed actions, leading to early …