A comparative evaluation of lung cancer using supervised learning methods

V Rawat, DP Singh, N Singh, S Poudel - AIP Conference Proceedings, 2023 - pubs.aip.org
The world leading fatal disease is lung cancer, with an annual rate of approximately 1.8
million. Lung cancer is a condition in which aberrant cells divide and grow rapidly …

Hybrid-feature-guided lung nodule type classification on CT images

J Yuan, X Liu, F Hou, H Qin, A Hao - Computers & Graphics, 2018 - Elsevier
In this paper, we propose a novel classification method for lung nodules from CT images
based on hybrid features. Towards nodules of different types, including well-circumscribed …

Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning

MA Talukder, MM Islam, MA Uddin, A Akhter… - Expert Systems with …, 2022 - Elsevier
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …

Revolutionizing Lung Cancer Diagnosis: A Comprehensive Review of Image Processing Techniques for Early Detection and Precision Medicine

SS Tippannavar, EA Madappa - Journal of Innovative Image …, 2023 - irojournals.com
Abstract According to World Health Organisation (WHO), lung cancer is the leading cause of
cancer-related fatalities in both genders and has the highest fatality rate. Early detection of …

Research on the auxiliary classification and diagnosis of lung cancer subtypes based on histopathological images

M Li, X Ma, C Chen, Y Yuan, S Zhang, Z Yan… - Ieee …, 2021 - ieeexplore.ieee.org
Lung cancer (LC) is one of the most serious cancers threatening human health.
Histopathological examination is the gold standard for qualitative and clinical staging of lung …

A feature engineering-based machine learning technique to detect and classify lung and colon cancer from histopathological images

I Chhillar, A Singh - Medical & Biological Engineering & Computing, 2024 - Springer
Globally, lung and colon cancers are among the most prevalent and lethal tumors. Early
cancer identification is essential to increase the likelihood of survival. Histopathological …

An improved convolution neural network and modified regularized K-Means-Based automatic lung nodule detection and classification

M Prakash - Journal of digital imaging, 2023 - pubmed.ncbi.nlm.nih.gov
If lung cancer is not detected in its initial phases, it can be fatal. However, because of the
quantity and structure of its nodules, lung cancer is difficult to detect early. For accurate …

An Improved Convolution Neural Network and Modified Regularized K-Means-Based Automatic Lung Nodule Detection and Classification.

M DL, M DP - Journal of Digital Imaging, 2023 - europepmc.org
If lung cancer is not detected in its initial phases, it can be fatal. However, because of the
quantity and structure of its nodules, lung cancer is difficult to detect early. For accurate …

[PDF][PDF] An Analysis on Advances In Lung Cancer Diagnosis With Medical Imaging And Deep Learning Techniques: Challenges And Opportunities

V SHARIFF, C PARITALA, KM ANKALA - Journal of Theoretical and Applied …, 2023 - jatit.org
This abstract provides an overview of numerous studies on the identification and diagnosis
of lung cancer using medical imaging and deep learning. However, techniques like the …

[PDF][PDF] Lung CT image recognition using deep learning techniques to detect lung cancer

P Chalasani, S Rajesh - Int. J. Emerg. Trends Eng. Res., 2020 - academia.edu
Now a days, The digital image recognition techniques are extensively used in a couple of
therapeutic domains for image improvement in earlier division and treatment stages, where …