Deep Learning in the Diagnosis of Lung Cancer

Authors

  • Aromal Sen Department of Computer Applications, Saintgits College of Applied Science, Kottayam, India
  • Shon J. Mathew Department of Computer Applications, Saintgits College of Applied Science, Kottayam, India
  • Ashley Mathew Department of Computer Applications, Saintgits College of Applied Science, Kottayam, India

Keywords:

Computer Aided Diagnosis (CAD), Lung Cancer, Deep Learning, Conventional Neural Network (CNN), LIDC, LSTM

Abstract

Cancer is one the deadliest disease and is regarded as the second dominant cause of death around the world with an estimated death of more than 9 million cases around the world and about 1 in 6 deaths is due to cancer. Lung Cancer is one the most common cancers that cannot be ignored and is one of the main reasons for the increase of deaths in the world among both women and men with an impressive rate of about five million. In recent few years, so many Computer Aided Diagnosis (CAD) are used for the detection of many diseases. Lung cancer detection in an early stage has been a crucial part for the sustainability of people’s life. So many experts and doctors use Deep Learning Techniques to determine the disease in the early stage itself. In this study we use Deep Learning techniques namely Convolutional Neural Network (CNN) for the lung cancer diagnosis and get the details in high efficient and accurate manner. The work done is a CNN network model with the help of LIDC dataset and LSTM network to analyze cancer nodules at early stages.

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Published

2021-03-28

How to Cite

[1]
A. Sen, S. J. Mathew, and A. Mathew, “Deep Learning in the Diagnosis of Lung Cancer”, IJRESM, vol. 4, no. 3, pp. 101–103, Mar. 2021.

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Articles