Enhanced lung cancer detection: Integrating improved random walker segmentation with artificial neural network and random forest classifier-Reference-Cited by-同舟云学术

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Enhanced lung cancer detection: Integrating improved random walker segmentation with artificial neural network and random forest classifier

Published:2024-04 Issue:7 Volume:10 Page:e29032
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Nair Sneha S.^ORCID,Devi V.N. Meena^ORCID,Bhasi Saju^ORCID

Publisher

Elsevier BV

Reference27 articles.

1. PRF-RW: a progressive random forest-based random walk approach for interactive semi-automated pulmonary lobes segmentation;Li;Int. J. Mach. Learn. Cybern.,2020

2. Pulomonary nodule classification from CT scan images using machine learning method;Rekha,2021

3. Random forest with self-paced bootstrap learning in lung cancer prognosis;Wang;ACM Trans. Multimed Comput. Commun. Appl,2020

4. An intelligent algorithm for lung cancer diagnosis using extracted features from Computerized Tomography images;Maleki;Healthcare Anal.,2023

5. Performance analysis of various machine learning-based approaches for detection and classification of lung cancer in humans;Singh;Neural Comput. Appl.,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer;Indian Journal of Surgical Oncology;2024-09-05

2. Optimizing lung cancer prediction: leveraging Kernel PCA with dendritic neural models;Computer Methods in Biomechanics and Biomedical Engineering;2024-07-13

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