A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics
Z Guo, L Xu, Y Si, N Razmjooy - International Journal of …, 2021 - Wiley Online Library
This study proposes a lung cancer diagnosis system based on computed tomography (CT)
scan images for the detection of the disease. The proposed method uses a sequential …
scan images for the detection of the disease. The proposed method uses a sequential …
Prediction and classification of lung cancer using machine learning techniques
P Chaturvedi, A Jhamb, M Vanani… - IOP conference series …, 2021 - iopscience.iop.org
In all the disease that have existed in mankind lung cancer has emerged as one of the most
fata one time and again. Also, it is one of the most common and contributing to deaths …
fata one time and again. Also, it is one of the most common and contributing to deaths …
HRDEL: High ranking deep ensemble learning-based lung cancer diagnosis model
Among all the diseases in human beings, lung cancer is known as the most hazardous
disease that often leads to death rather than other cancer ailments. Lung cancer is …
disease that often leads to death rather than other cancer ailments. Lung cancer is …
Detection and classification of lung cancer computed tomography images using a novel improved deep belief network with Gabor filters
EA Siddiqui, V Chaurasia, M Shandilya - Chemometrics and Intelligent …, 2023 - Elsevier
The computer-aided diagnosis (CAD) method plays a considerable role in the automated
recognition of medical images, considering the increasing numbers of lung cancer patients …
recognition of medical images, considering the increasing numbers of lung cancer patients …
ISANET: Non-small cell lung cancer classification and detection based on CNN and attention mechanism
Z Xu, H Ren, W Zhou, Z Liu - Biomedical Signal Processing and Control, 2022 - Elsevier
Lung cancer is one of the malignant tumors with high morbidity and mortality worldwide.
Among them, non-small cell lung cancer accounts for about 85% of all lung cancers. In the …
Among them, non-small cell lung cancer accounts for about 85% of all lung cancers. In the …
[HTML][HTML] An intelligent algorithm for lung cancer diagnosis using extracted features from Computerized Tomography images
Abstract According to the World Health Organization, lung cancer is a leading cause of
death worldwide. This research aims to process the Computerized Tomography (CT) images …
death worldwide. This research aims to process the Computerized Tomography (CT) images …
COVID-19 detection on chest X-ray images with the proposed model using artificial intelligence and classifiers
Abstract Coronavirus disease-2019 (COVID-19) is a serious infectious disease that is
spreading rapidly all over the world. Scientists are looking for alternative diagnostic methods …
spreading rapidly all over the world. Scientists are looking for alternative diagnostic methods …
State-of-the-art in 1D Convolutional Neural Networks: A survey
Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …
most common approach being the Convolutional Neural Network (CNN). Through CNN …