Deep learning - cancer genetics and application of deep learning to cancer oncology

Doan Hoang, Simon Hoang
Author affiliations

Authors

  • Doan Hoang School of Electrical and Data Engineering, University of Technology Sydney, 15 Broadway,Ultimo, NSW2007, Australia
  • Simon Hoang Sydney Local Health District, Sydney, NSW 2137, Australia

DOI:

https://doi.org/10.15625/2525-2518/17256

Keywords:

deep learning, cancer genetics, cancer oncology, drug response prediction, deep learning applications

Abstract

Arguably the human body has been one of the most sophisticated systems we encounter but until now we are still far from understanding its complexity. We have been trying to replicate human intelligence by way of artificial intelligence but with limited success. We have discovered the molecular structure in terms of genetics, performed gene editing to change an organism’s DNA and much more, but their translatability into the field of oncology has remained limited. Conventional machine learning methods achieved some degree of success in solving problems that we do not have an explicit algorithm. However, they are basically shallow learning methods, not rich enough to discover and extract intricate features that represent patterns in the real environment. Deep learning has exceeded human performance in pattern recognition as well as strategic games and are powerful for dealing with many complex problems. High-throughput sequencing and microarray techniques have generated vast amounts of data and allowed the comprehensive study of gene expression in tumor cells. The application of deep learning with molecular data enables applications in oncology with information not available from clinical diagnosis. This paper provides fundamental concepts of deep learning, an essential knowledge of cancer genetics, and a review of applications of deep learning to cancer oncology. Importantly, it provides an insightful knowledge of deep learning and an extensive discussion on its challenges. The ultimate purpose is to germinate ideas and facilitate collaborations between cancer biologists and deep learning researchers to address challenging oncological problems using advanced deep learning technologies.

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Published

30-12-2022

How to Cite

[1]
D. Hoang and S. Hoang, “Deep learning - cancer genetics and application of deep learning to cancer oncology”, Vietnam J. Sci. Technol., vol. 60, no. 6, pp. 885–928, Dec. 2022.

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Review