[HTML][HTML] MENet: A Mitscherlich function based ensemble of CNN models to classify lung cancer using CT scans
Lung cancer is one of the leading causes of cancer-related deaths worldwide. To reduce the
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
[HTML][HTML] Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Lung cancer (LC) remains a leading cause of death worldwide. Early diagnosis is critical to
protect innocent human lives. Computed tomography (CT) scans are one of the primary …
protect innocent human lives. Computed tomography (CT) scans are one of the primary …
[HTML][HTML] Unified deep learning models for enhanced lung cancer prediction with ResNet-50–101 and EfficientNet-B3 using DICOM images
Significant advancements in machine learning algorithms have the potential to aid in the
early detection and prevention of cancer, a devastating disease. However, traditional …
early detection and prevention of cancer, a devastating disease. However, traditional …
Comparative hybrid deep convolutional learning framework with transfer learning for diagnosis of lung cancer
Lung cancer stands as the most common cancer in men and has 2 nd rank in women
worldwide. Detecting the type of cancer and running the appropriate treatments in the early …
worldwide. Detecting the type of cancer and running the appropriate treatments in the early …
LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data
Lung cancer, also known as pulmonary cancer, is one of the deadliest cancers, but yet
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
Detection of lung cancers from ct images using a deep CNN architecture in layers through ML
Lung inflammation is caused by the development of cancer cells. As the frequency of cancer
rises, men and women are dying at a higher rate. With malignancy, cancerous cells multiply …
rises, men and women are dying at a higher rate. With malignancy, cancerous cells multiply …
Lung cancer diagnosis based on convolutional neural networks ensemble model
L Lyu - 2021 2nd International Seminar on Artificial …, 2021 - ieeexplore.ieee.org
Lung cancer is a lethal disease that can be treated efficiently if diagnosed in an early stage.
Screening is a technology involving using CT scan to diagnose whether the lung is attacked …
Screening is a technology involving using CT scan to diagnose whether the lung is attacked …
A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets
P Mukherjee, M Zhou, E Lee, A Schicht… - Nature machine …, 2020 - nature.com
Lung cancer is the most common fatal malignancy in adults worldwide, and non-small-cell
lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography is …
lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography is …
Lcdctcnn: Lung cancer diagnosis of ct scan images using cnn based model
The most deadly and life-threatening disease in the world is lung cancer. Though early
diagnosis and accurate treatment are necessary for lowering the lung cancer mortality rate …
diagnosis and accurate treatment are necessary for lowering the lung cancer mortality rate …
Lung cancer detection from thoracic CT scans using an ensemble of deep learning models
Lung cancer remains a prevalent and deadly disease, claiming numerous lives annually.
Early detection plays a pivotal role in significantly improving survival rates, by up to 50–70 …
Early detection plays a pivotal role in significantly improving survival rates, by up to 50–70 …