Malignancy detection in lung and colon histopathology images using transfer learning with class selective image processing
Cancer accounts for a huge mortality rate due to its aggressiveness, colossal potential of
metastasis, and heterogeneity (causing resistance against chemotherapy). Lung and colon …
metastasis, and heterogeneity (causing resistance against chemotherapy). Lung and colon …
Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
An explainable classification method based on complex scaling in histopathology images for lung and colon cancer
Lung and colon cancers are among the leading causes of human mortality and morbidity.
Early diagnostic work up of these diseases include radiography, ultrasound, magnetic …
Early diagnostic work up of these diseases include radiography, ultrasound, magnetic …
A machine learning approach to diagnosing lung and colon cancer using a deep learning-based classification framework
The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
A deep model for lung cancer type identification by densely connected convolutional networks and adaptive boosting
S Pang, Y Zhang, M Ding, X Wang, X Xie - IEEE Access, 2019 - ieeexplore.ieee.org
Timely diagnosis and determination to the type of lung cancer has important clinical
significance. Generally, it requires multiple imaging methods to complement each other to …
significance. Generally, it requires multiple imaging methods to complement each other to …
A transfer learning approach with a convolutional neural network for the classification of lung carcinoma
Lung cancer is among the most hazardous types of cancer in humans. The correct diagnosis
of pathogenic lung disease is critical for medication. Traditionally, determining the …
of pathogenic lung disease is critical for medication. Traditionally, determining the …
Colorectal histology tumor detection using ensemble deep neural network
S Ghosh, A Bandyopadhyay, S Sahay, R Ghosh… - … Applications of Artificial …, 2021 - Elsevier
With a mortality rate of approximately 33.33%, Colorectal cancer serves as the second most
prevalent malignant tumor type in the world. AI-guided clinical care/tool can help in reducing …
prevalent malignant tumor type in the world. AI-guided clinical care/tool can help in reducing …
Automated classification of lung cancer types from cytological images using deep convolutional neural networks
A Teramoto, T Tsukamoto, Y Kiriyama… - BioMed research …, 2017 - Wiley Online Library
Lung cancer is a leading cause of death worldwide. Currently, in differential diagnosis of
lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell …
lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell …
[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 …
A regularized ensemble framework of deep learning for cancer detection from multi-class, imbalanced training data
X Yuan, L Xie, M Abouelenien - Pattern Recognition, 2018 - Elsevier
In medical diagnosis, eg bowel cancer detection, a large number of examples of normal
cases exists with a much smaller number of positive cases. Such data imbalance usually …
cases exists with a much smaller number of positive cases. Such data imbalance usually …