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The application and challenges of artificial intelligence in brain tumor recognition
- 1 Macquarie University
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Abstract
There is no denying the fact that Artificial intelligence technology has developed rapidly in recent years. In medicine, especially in brain tumor detection field, it has attracted great attention. By combining artificial intelligence with physiological imaging, the classification of brain tumors and the selection of the best treatment options can become more accurate and precise. AI brain tumor detection can reduce the rate of misdiagnosis and improve the speed of diagnosis. The article researches the method of AI in brain tumor detection. The process of the general method can be divided into four phases: Data collection, Preprocessing, Feature extraction, and Classification. At the same time, this article also analyzes the application of AI in brain tumor detection and treatment, including the advantages and challenges of AI application, development direction, and conclusions. As a review paper, this paper provides a relatively complete overview of this field. Even though the growing presence of AI technology in the brain tumor medical field is already bringing greater assistance, there is still a lot of room to improve. Indeed, a highly accurate, explainable system is needed in the future. With the rapid development of AI methods, so do the corresponding high-performance hardware become increasingly essential.
Keywords
brain tumor detection, artificial intelligence, machine learning
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Cite this article
Han,Z. (2023). The application and challenges of artificial intelligence in brain tumor recognition. Applied and Computational Engineering,17,17-22.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Computing and Data Science
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