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 approach to classify lung and colon cancer of histopathology images using deep feature extraction and an ensemble method
Cancer is a deadly condition brought on by a range of metabolic anomalies and genetic
disorders. Lung and colon cancer in particular is among the leading causes of death and …
disorders. Lung and colon cancer in particular is among the leading causes of death and …
An extensive review on lung cancer diagnosis using machine learning techniques on radiological data: state-of-the-art and perspectives
Cancer of the lung is a killer illness that often results from a combination of genetic
disposition and many clinical changes. The lung region of the body contains cancerous cells …
disposition and many clinical changes. The lung region of the body contains cancerous cells …
[HTML][HTML] 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 …
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 …
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 …
[HTML][HTML] 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 …
[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 …