Enhancing lung cancer diagnosis with data fusion and mobile edge computing using DenseNet and CNN

Enhancing lung cancer diagnosis with data fusion and mobile edge computing using DenseNet and CNN

Abstract The recent advancements in automated lung cancer diagnosis through the application of Convolutional Neural Networks (CNN) on Computed Tomography (CT) scans have marked a significant leap in medical imaging and diagnostics. The precision of these CNN-based classifiers in detecting and analyz...

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Bibliographic Details
Main Authors: Chengping Zhang, Muhammad Aamir, Yurong Guan, Muna Al-Razgan, Emad Mahrous Awwad, Rizwan Ullah, Uzair Aslam Bhatti, Yazeed Yasin Ghadi
Format: Article
Language:English
Published: SpringerOpen 2024-04-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
DenseNet
Convolutional neural network
Lungs classification
Online Access:https://doi.org/10.1186/s13677-024-00597-w

Internet

https://doi.org/10.1186/s13677-024-00597-w

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