Lung cancer diagnosis based on an ann optimized by improved teo algorithm

R Shan, T Rezaei - Computational Intelligence and …, 2021 - Wiley Online Library
A quarter of all cancer deaths are due to lung cancer. Studies show that early diagnosis and
treatment of this disease are the most effective way to increase patient life expectancy. In this …

Lung cancer detection using enhanced segmentation accuracy

O Akter, MA Moni, MM Islam, JMW Quinn… - Applied Intelligence, 2021 - Springer
Lung cancer is currently one of the most common causes of cancer-related death. Detecting
and providing an accurate diagnosis of potentially cancerous lung nodules at an early stage …

Automatic segmentation and classification of lung tumour using advance sequential minimal optimisation techniques

K Vijila Rani, S Joseph Jawhar - IET Image Processing, 2020 - Wiley Online Library
A chronic disorder caused by abnormal growth of the lung cells in the pulmonary tumour.
This study suggests a modern automated approach to improve efficiency and decrease the …

Automated lung cancer diagnosis using swarm intelligence with deep learning

N Shaikh, P Shah - Computer Methods in Biomechanics and …, 2023 - Taylor & Francis
In worldwide, lung cancer is amajor threatening issue for humans that increase the mortality
rate. Here, the existing techniques are suffered from huge false-positiverates. Such kind of …

[PDF][PDF] A Systematic Review of Artificial Intelligence Techniques in Lung Cancer Detection and Accurate Diagnosis.

R Gangal, P Johri, A Kumar - Cosmos Journal of Engineering & …, 2023 - cosmosjournal.in
Lung cancer, which has the greatest fatality rate of any cancer kind, is the most serious form
of the disease. Many lives may be saved by early detection. Along with breast cancer in …

[PDF][PDF] Improving Lungs Cancer Detection Based on Hybrid Features and Employing Machine Learning Techniques

J Yang, L Yee, AA Khan, MS Khan, H Karamti… - 2023 - assets-eu.researchsquare.com
Lung cancer detection using machine learning involves training a model on a dataset of
medical images, such as CT scans, to identify patterns and features associated with lung …

[PDF][PDF] Novel Contiguous Cross Propagation Neural Network Built CAD for Lung Cancer.

AA Blessie, P Ramesh - Computer Systems Science & …, 2023 - cdn.techscience.cn
The present progress of visual-based detection of the diseased area of a malady plays an
essential part in the medical field. In that case, the image processing is performed to improve …

Novel image markers for non-small cell lung cancer classification and survival prediction

H Wang, F Xing, H Su, A Stromberg, L Yang - BMC bioinformatics, 2014 - Springer
Background Non-small cell lung cancer (NSCLC), the most common type of lung cancer, is
one of serious diseases causing death for both men and women. Computer-aided diagnosis …

Diagnosis of lung and colon cancer based on clinical pathology images using convolutional neural network and CLAHE framework

S Hadiyoso, S Aulia, ID Irawati - International Journal of Applied …, 2023 - gigvvy.com
Cancer is a non-contagious disease that is the leading cause of death globally. The most
common types of cancer with high mortality are lung and colon cancer. One of the efforts to …

Comprehensive and comparative global and local feature extraction framework for lung cancer detection using CT scan images

MA Alzubaidi, M Otoom, H Jaradat - IEEE Access, 2021 - ieeexplore.ieee.org
Lung cancer is reported to be the second most common cancer disease. This paper
proposes a comprehensive and comparative global and local feature extraction framework …