International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Lung Cancer Detection Using Machine Learning and Deep Learning Techniques

Abstract

Early recognition of Cell disintegration in the lungs cells can help in a sharp lessening in the lung cancer death rate subsequently it is a forceful infection which conveying a bleak forecast with a 5-year endurance rate at 18%. Several PC supported determination substructures have been created to help diminish Cell disintegration in the lungs death rates. Thus, structural co-occurrence matrix - based methodology is utilized to separate the component & to characterize tumors into dangerous or considerate tumors & furthermore into their threat level. The computed tomography examines from the lung picture details base consortium & picture data set asset activity datasets give details regarding clot locations & their harm levels is been conveyed here as a model. Support vector machine & CNN is being utilized as a classifier which seems to be 1) to categories the clot pictures into threatening or benevolent clots & 2) to arrange the lung clots into harm levels. These test results uncover that the SCM effectively removed highlights of the clots from the pictures &, in this manner might be regarded as a propitious device to help clinical expert to make a more exact discover regarding the danger of lung clots.

Country : India

1 Nazia Fatima2 Ayonija Pathre3 Mukesh Kumar

  1. Student, Department of Computer Science, Rabindranath Tagore University, Bhopal, MP, India
  2. Assistant Professor, Department of Computer Science, Rabindranath Tagore University, Bhopal, MP, India
  3. Assistant Professor, Department of Computer Science, Rabindranath Tagore University, Bhopal, MP, India

IRJIET, Volume 5, Issue 2, February 2021 pp. 34-42

doi.org/10.47001/IRJIET/2021.502006

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