Deep learning for colon cancer histopathological images analysis

AB Hamida, M Devanne, J Weber, C Truntzer… - Computers in Biology …, 2021 - Elsevier
Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours.
Unfortunately, existing methods remain limited when faced with the high resolution and size …

Artificial intelligence in lung cancer pathology image analysis

S Wang, DM Yang, R Rong, X Zhan, J Fujimoto, H Liu… - Cancers, 2019 - mdpi.com
Objective: Accurate diagnosis and prognosis are essential in lung cancer treatment
selection and planning. With the rapid advance of medical imaging technology, whole slide …

[PDF][PDF] Lung cancer detection using convolutional neural network on histopathological images

BK Hatuwal, HC Thapa - Int. J. Comput. Trends Technol, 2020 - researchgate.net
Lung Cancer is one of the leading life taking cancer worldwide. Early detection and
treatment are crucial for patient recovery. Medical professionals use histopathological …

Application of artificial intelligence in lung cancer

HY Chiu, HS Chao, YM Chen - Cancers, 2022 - mdpi.com
Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

The state of the art for artificial intelligence in lung digital pathology

VS Viswanathan, P Toro, G Corredor… - The Journal of …, 2022 - Wiley Online Library
Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of
digital pathology (DP) and an increase in computational power have led to the development …

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 …

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 …

[HTML][HTML] A narrative review of digital pathology and artificial intelligence: focusing on lung cancer

T Sakamoto, T Furukawa, K Lami… - Translational Lung …, 2020 - ncbi.nlm.nih.gov
The emergence of whole slide imaging technology allows for pathology diagnosis on a
computer screen. The applications of digital pathology are expanding, from supporting …

New bidirectional recurrent neural network optimized by improved Ebola search optimization algorithm for lung cancer diagnosis

MH Sabzalian, F Kharajinezhadian, AR Tajally… - … Signal Processing and …, 2023 - Elsevier
The early detection of cancerous and malignant lung cancer by medical imaging techniques,
CT-scan for example, which never needs to do sampling reduces the risk of cancer growth …

Deep transfer learning based model for colorectal cancer histopathology segmentation: A comparative study of deep pre-trained models

SH Kassani, PH Kassani, MJ Wesolowski… - International Journal of …, 2022 - Elsevier
Colorectal cancer is one of the leading causes of cancer-related death, worldwide. Early
detection of suspicious tissues can significantly improve the survival rate. In this study, the …