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Analyzing the Impact of Machine Learning on Cancer Treatments

Author

Listed:
  • Victor Chang

    (Aston University, UK)

  • Gunji Srilikhita

    (Teesside University, UK)

  • Qianwen Ariel Xu

    (Teesside University, UK)

  • M. A. Hossain

    (Cambodia University of Technology and Science, Cambodia)

  • Mohsen Guizani

    (Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI))

Abstract

The survival rate of breast cancer prediction has been a significant issue for researchers. Nowadays, the health care industry has completely transformed by using modern technologies and their applications for medical services. Among those technologies, machine learning is one of them, which has gained attention by people that its new advanced technology would give accurate results by using modeling methods for prediction. As this is a branch of artificial intelligence, it employs various statics, probabilistic and optimistic tools. This is applied to medical services, especially which are based on proteomic and genomic measurements. The aim is to use the dataset of cancer treatment and predict the results of patients by using machine learning with its modeling methods for accurate results. Recently experts have even used this machine learning in cancer for prognosis and forecasting.

Suggested Citation

  • Victor Chang & Gunji Srilikhita & Qianwen Ariel Xu & M. A. Hossain & Mohsen Guizani, 2022. "Analyzing the Impact of Machine Learning on Cancer Treatments," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 13(1), pages 1-22, January.
    • Handle: RePEc:igg:jdst00:v:13:y:2022:i:1:p:1-22
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