Green synthesis of nanomaterials for early lung cancer detection

Lung cancer is the foremost cause of cancer-related deaths world-wide [1]. It affects 100,000 Americans of the smoking population every year of all age groups, particularly those above 50 years of the smoking population [2]. In India, 51,000 lung cancer deaths were reported in 2012, which include 41,000 men and 10,000 women [3]. It is the leading cause of cancer deaths in men; however, in women, it ranked ninth among all cancerous deaths [4]. It is possible to detect the lung cancer at a very early stage, providing a much higher chance of survival for the patients.

2018 ◽  
Vol 39 (1) ◽  
pp. 45-55 ◽  
Author(s):  
Terunaga Inage ◽  
Takahiro Nakajima ◽  
Ichiro Yoshino ◽  
Kazuhiro Yasufuku

2018 ◽  
Vol 24 (13) ◽  
pp. 2984-2992 ◽  
Author(s):  
Ehab Billatos ◽  
Jessica L. Vick ◽  
Marc E. Lenburg ◽  
Avrum E. Spira

2018 ◽  
Vol 5 (1) ◽  
pp. 24-30
Author(s):  
Fatema Tuj Johora ◽  
Mehdi Hassan Jony ◽  
Md Shakhawat Hossain ◽  
Humayun Kabir Rana

Lung cancer is one of the most dangerous diseases and prediction of it, is the most challenging problem nowadays. Most of the cancer cells are overlapped with each other. It is hard to detect the cells but also essential to identify the presence of cancer cells in the early stage. Early detection of lung cancer may reduce the death rate. In this study, we used the Grey Level Co-occurrence Matrix (GLCM) to extract the feature of cancer affected lung image and then Support Vector Machine (SVM) has been used to detect normal and abnormal lung cells after implementing the features. Our experimental evaluation using MATLAB demonstrates the efficient performance of the proposed system and in the result. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 5(1), Dec 2018 P 24-30


Cancer ◽  
2000 ◽  
Vol 89 (S11) ◽  
pp. 2327-2328 ◽  
Author(s):  
Robert A. Smith ◽  
Thomas J. Glynn

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