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 …
[HTML][HTML] Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey
Lung cancer is among the deadliest cancers. Besides lung nodule classification and
diagnosis, develo** non-invasive systems to classify lung cancer histological …
diagnosis, develo** non-invasive systems to classify lung cancer histological …
RETRACTED ARTICLE: A MobileNet-based CNN model with a novel fine-tuning mechanism for COVID-19 infection detection
COVID-19 is a virus that causes upper respiratory tract and lung infections. The number of
cases and deaths increased daily during the pandemic. Once it is vital to diagnose such a …
cases and deaths increased daily during the pandemic. Once it is vital to diagnose such a …
A new lung cancer detection method based on the chest CT images using Federated Learning and blockchain systems
A Heidari, D Javaheri, S Toumaj, NJ Navimipour… - Artificial Intelligence in …, 2023 - Elsevier
With an estimated five million fatal cases each year, lung cancer is one of the significant
causes of death worldwide. Lung diseases can be diagnosed with a Computed Tomography …
causes of death worldwide. Lung diseases can be diagnosed with a Computed Tomography …
Lung cancer detection from CT scans using modified DenseNet with feature selection methods and ML classifiers
MG Lanjewar, KG Panchbhai, P Charanarur - Expert Systems with …, 2023 - Elsevier
Lung cancer is a highly life-threatening disease worldwide, and detection is crucial. In this
study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four …
study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four …
Cloud‐Based Lung Tumor Detection and Stage Classification Using Deep Learning Techniques
G Kasinathan, S Jayakumar - Biomed research international, 2022 - Wiley Online Library
Artificial intelligence (AI), Internet of Things (IoT), and the cloud computing have recently
become widely used in the healthcare sector, which aid in better decision‐making for a …
become widely used in the healthcare sector, which aid in better decision‐making for a …
Deep learning techniques for cancer classification using microarray gene expression data
Cancer is one of the top causes of death globally. Recently, microarray gene expression
data has been used to aid in cancer's effective and early detection. The use of DNA …
data has been used to aid in cancer's effective and early detection. The use of DNA …
[Retracted] Prediction Performance of Deep Learning for Colon Cancer Survival Prediction on SEER Data
S Gupta, S Kalaivani, A Rajasundaram… - BioMed Research …, 2022 - Wiley Online Library
Colon and rectal cancers are the most common kinds of cancer globally. Colon cancer is
more prevalent in men than in women. Early detection increases the likelihood of survival …
more prevalent in men than in women. Early detection increases the likelihood of survival …
COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images
Abstract COVID-19 (SARS-CoV-2), which causes acute respiratory syndrome, is a
contagious and deadly disease that has devastating effects on society and human life …
contagious and deadly disease that has devastating effects on society and human life …
Enhanced Elman spike Neural network optimized with flamingo search optimization algorithm espoused lung cancer classification from CT images
At present, researchers have been try to enhance the CAD system performance utilizing
deep learning techniques in lung cancer screening and computed tomography (CT), but …
deep learning techniques in lung cancer screening and computed tomography (CT), but …