IoT with cloud based lung cancer diagnosis model using optimal support vector machine

D Valluru, IJS Jeya - Health care management science, 2020 - Springer
In the last decade, exponential growth of Internet of Things (IoT) and cloud computing takes
the healthcare services to the next level. At the same time, lung cancer is identified as a …

[PDF][PDF] Lung cancer prediction using deep learning framework

RR Subramanian, RN Mourya, VPT Reddy… - … Journal of Control …, 2020 - researchgate.net
Lung carcinoma also known as lung cancer is one of the dangerous diseases caused all
over the world. It is caused due to the reluctant increase of cells in the lung tissues. It is …

An enhanced grey wolf optimization based feature selection wrapped kernel extreme learning machine for medical diagnosis

Q Li, H Chen, H Huang, X Zhao, ZN Cai… - … methods in medicine, 2017 - Wiley Online Library
In this study, a new predictive framework is proposed by integrating an improved grey wolf
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …

[HTML][HTML] CanDiag: fog empowered transfer deep learning based approach for cancer diagnosis

A Pati, M Parhi, BK Pattanayak, B Sahu, S Khasim - Designs, 2023 - mdpi.com
Breast cancer poses the greatest long-term health risk to women worldwide, in both
industrialized and developing nations. Early detection of breast cancer allows for treatment …

Lung cancer disease detection using service-oriented architectures and multivariate boosting classifier

T Chandrasekar, SK Raju, M Ramachandran… - Applied Soft …, 2022 - Elsevier
Big data analytics in healthcare is emerging as a promising field to extract valuable
information from large databases and enhance results with fewer costs. Although numerous …

A systematic review of modern approaches in healthcare systems for lung cancer detection and classification

SK Pandey, AK Bhandari - Archives of Computational Methods in …, 2023 - Springer
Lung cancer has become a prevalent form of cancer; it can be found in persons of all age
groups. The early stage identification of lung cancer is required to control the integrated …

[HTML][HTML] RETRACTED ARTICLE: Evolving deep convolutional neutral network by hybrid sine–cosine and extreme learning machine for real-time COVID19 diagnosis …

C Wu, M Khishe, M Mohammadi, SH Taher Karim… - Soft Computing, 2023 - Springer
The COVID19 pandemic globally and significantly has affected the life and health of many
communities. The early detection of infected patients is effective in fighting COVID19. Using …

An analysis of deep transfer learning-based approaches for prediction and prognosis of multiple respiratory diseases using pulmonary images

A Koul, RK Bawa, Y Kumar - Archives of Computational Methods in …, 2024 - Springer
Respiratory diseases can lead to lung failure, which happens when the lungs cannot give
the body enough oxygen. These diseases can be diagnosed using medical data, lung …

A comprehensive review on federated learning based models for healthcare applications

S Sharma, K Guleria - Artificial Intelligence in Medicine, 2023 - Elsevier
A disease is an abnormal condition that negatively impacts the functioning of the human
body. Pathology determines the causes behind the disease and identifies its development …

Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification

SK Baliarsingh, S Vipsita - IET Systems Biology, 2020 - Wiley Online Library
Microarray technology plays a significant role in cancer classification, where a large number
of genes and samples are simultaneously analysed. For the efficient analysis of the …