Study on segmentation and prediction of lung cancer based on machine learning approaches
Journal Title: International Journal of Experimental Research and Review - Year 2022, Vol 30, Issue 1
Abstract
Lung cancer is a dangerous disease in human health. At the early stage, lung cancer detection provides a way to save human life. As a result, improvements in Deep Learning (DL), a technique, a branch of Machine Learning (ML), have helped to identify and classify lung cancer in clinical photographs. DL technology has also outperformed traditional methods in a variety of fields. Researchers are exploring various DL techniques for disease detection to improve the accuracy of the CAD systems in CT lung cancer detection. In this experiment, cutting-edge ML and DL methods for lung disease have been recommended as CAD systems after thoroughly analysing existing frameworks. It can be separated into FP reduction systems and system to detect nodule. The primary characteristics of various approaches are analyzed. The CT lung datasets existing for examination and evaluation with the various approaches are also presented and discussed.
Authors and Affiliations
Anindita Saha, Rakesh Kumar Yadav
Keywords
Related Articles
- EP ID EP715425
- DOI https://doi.org/10.52756/ijerr.2023.v30.001
- Views 67
- Downloads 0
An IoT-based soil analysis system using optical sensors and multivariate regression
Food is the primary requirement for the survival of any living being on this planet. The rapid increment in the population is a major concern for adequate food production due to the depletion of agricultural land, which...
Metal-free one-pot oxidative conversion: Molecular Iodine Mediated Oxidation Organic Reactions
arious oxidative compounds such as aldehyde, ketone ester, and acids can be produced in large yields by an effective iodine-mediatedoxidative reaction of organic mol-ecules. Molecular iodine is a generall...
Current Understating of Gut Microbiome Alterations and Therapeutic Approaches for Improving Human Health
Millions of microorganisms, including bacteria, fungi, and viruses compose the human gut microbiome. There is variation in the composition of species from the moment of birth throughout the whole human lifecycle. Gut mic...
Impact of Entrepreneurial Ecosystem on Sustainable Social Enterprises – A Mixed-Methods Research
The main objective of this study is to identify the challenges faced by social entrepreneurs concerning the social entrepreneurial ecosystem that exists in India and suggest policy recommendations to create an enabling e...
Sugarcane Diseases Detection Using Optimized Convolutional Neural Network with Enhanced Environmental Adaptation Method
This research aims to address the need for accurate and prompt identification of sugarcane diseases, which substantially impact the worldwide sugar industry and the livelihoods of numerous farmers. Conventional visual in...