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Implementation of Artificial Intelligence Techniques for Cancer Detection


Diseases like cancer have been termed as chronic fatal disease because of its deadly nature. The reason why cancer is termed as fatal is cancer progresses faster, and in most of the cases, these cells are detected at an advance stage. It is found that early detection of cancer is the key to lower death rate. In this study, overviews of applying AI technology for diagnosis of three types of cancer, breast, lung and liver, have been demonstrated. Various studies are reviewed for the different types of systems which are used for early detection of cancer. Automated or computer-aided systems with AI are considered as they provide a perfect fit to process a large dataset with accuracy and efficiency in detecting cancer. Diagnosis and treatment can be carried out with the help of these systems. Breast, lung and liver cancer studies have shown that some of these systems provide accurate precision in diagnosis and thus can solve the problem if these systems are implemented. However, these systems have to face a lot of hurdles to be implemented on a large scale. Image preprocessing, data management and other technology also need enhancement to be compatible with AI and machine learning algorithms to be implemented. Considering the experimental results, this study shows there is no doubt that the AI-implemented neural networks would be the future in cancer diagnosis and treatment.

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The authors are grateful to Indus University and School of Technology, Pandit Deendayal Petroleum University, for the permission to publish this research.


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All the authors make substantial contribution in this manuscript. DP, YS, NT, KS and MS participated in drafting the manuscript. DP, YS, NT and KS wrote the main manuscript. All the authors discussed the results and implication on the manuscript at all stages.

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Correspondence to Manan Shah.

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Patel, D., Shah, Y., Thakkar, N. et al. Implementation of Artificial Intelligence Techniques for Cancer Detection. Augment Hum Res 5, 6 (2020).

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  • Artificial intelligence
  • Health care
  • Cancer
  • Detection