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Deep Learning Techniques in Perception of Cancer Diagnosis

Deep Learning Techniques in Perception of Cancer Diagnosis

Anshul, Raju Kumar
Copyright: © 2021 |Pages: 20
ISBN13: 9781799875116|ISBN10: 1799875113|ISBN13 Softcover: 9781799883586|EISBN13: 9781799875178
DOI: 10.4018/978-1-7998-7511-6.ch001
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MLA

Anshul, and Raju Kumar. "Deep Learning Techniques in Perception of Cancer Diagnosis." Examining the Impact of Deep Learning and IoT on Multi-Industry Applications, edited by Roshani Raut and Albena Dimitrova Mihovska, IGI Global, 2021, pp. 1-20. https://doi.org/10.4018/978-1-7998-7511-6.ch001

APA

Anshul & Kumar, R. (2021). Deep Learning Techniques in Perception of Cancer Diagnosis. In R. Raut & A. Mihovska (Eds.), Examining the Impact of Deep Learning and IoT on Multi-Industry Applications (pp. 1-20). IGI Global. https://doi.org/10.4018/978-1-7998-7511-6.ch001

Chicago

Anshul, and Raju Kumar. "Deep Learning Techniques in Perception of Cancer Diagnosis." In Examining the Impact of Deep Learning and IoT on Multi-Industry Applications, edited by Roshani Raut and Albena Dimitrova Mihovska, 1-20. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-7511-6.ch001

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Abstract

In this era of technology, for effective treatment of patients, clinical experts are getting great support from automated e-healthcare systems. Nowadays, one of the leading reasons of death is cancer. Some common cancers are breast cancer, prostate cancer, lung cancer, skin cancer, brain cancer, and so on. To save human lives from cancer, an effective and timely treatment is required. Many different types of image modalities like CT scan, ultrasound, x-ray, MRI can be used to determine the disease, but traditionally, this was purely dependent on the knowledge and experience of doctors. So, the death rate was quite high and increasing day by day. Machine learning and deep learning are providing robust solutions in this field. There are many deep learning techniques like RNN, CNN, DBN, autoencoders, generative adversarial networks which are providing robust solutions in cancer diagnosis and prognosis so that many human lives can be saved. The objective of this chapter is to give an insight into deep learning techniques in the field of a cancer diagnosis.

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