A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and Diagnosis

Archives of Computational Methods in Engineering - Tập 29 - Trang 2043-2070 - 2021
Yogesh Kumar1, Surbhi Gupta2, Ruchi Singla3, Yu-Chen Hu4
1Department of Computer Engineering, Indus Institute of Technology & Engineering, Indus University , Ahmedabad, India
2School of Computer Science and Engineering, Model Institute of Engineering and Technology, Jammu, India
3Department of Research, Innovations, Sponsored Projects and Entrepreneurship, Chandigarh Group of Colleges, Landran, India
4Department of Computer Science and Information Management, Providence University, Taichung City, Taiwan, ROC

Tóm tắt

Artificial intelligence has aided in the advancement of healthcare research. The availability of open-source healthcare statistics has prompted researchers to create applications that aid cancer detection and prognosis. Deep learning and machine learning models provide a reliable, rapid, and effective solution to deal with such challenging diseases in these circumstances. PRISMA guidelines had been used to select the articles published on the web of science, EBSCO, and EMBASE between 2009 and 2021. In this study, we performed an efficient search and included the research articles that employed AI-based learning approaches for cancer prediction. A total of 185 papers are considered impactful for cancer prediction using conventional machine and deep learning-based classifications. In addition, the survey also deliberated the work done by the different researchers and highlighted the limitations of the existing literature, and performed the comparison using various parameters such as prediction rate, accuracy, sensitivity, specificity, dice score, detection rate, area undercover, precision, recall, and F1-score. Five investigations have been designed, and solutions to those were explored. Although multiple techniques recommended in the literature have achieved great prediction results, still cancer mortality has not been reduced. Thus, more extensive research to deal with the challenges in the area of cancer prediction is required.

Tài liệu tham khảo

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