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• W4285278045 abstract "Millions of death cases have been occurring from liver cancer or hepatic cancer worldwide. This disease is most commonly caused by scarring or cirrhosis of the liver tissue. Therefore, the early detection of liver cancer is very important for timely treatment and saving the patient’s life. However, it is challenging to detect and characterize liver cancer manually. Consequently, artificial intelligence (AI) techniques such as automated liver cancer detection services are now available in the medical field for the detection and treatment of this cancer. This review evaluates several types of researches and advanced technologies that can help to diagnose liver cancer automatically. Through this review of 26 relevant articles, the following synthesis of liver cancer detection techniques have been produced: (a) the use of machine learning (ML) and deep learning (DL) methods, and (b) the use of classical imaging technologies. Finally, it is found that the latest Deep Learning (DL) classifiers are capable of detecting liver cancer accurately, fastly, and reliably. However, a major problem with existing relevant articles is that there is a lack of publicly available datasets for the detection of liver cancer and the drawback of these datasets is that almost all have few images. Hence, further research should be performed on large publicly available datasets to improve the complexity of computation for reliable diagnosis of liver cancer. As a result, it serves mankind much better in efficiency and cost-effectiveness." @default.
• W4285278045 created "2022-07-14" @default.
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• W4285278045 date "2022-01-01" @default.
• W4285278045 modified "2023-10-12" @default.
• W4285278045 title "Automatic Detection of Liver Cancer Using Artificial Intelligence and Imaging Techniques—A Review" @default.
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• W4285278045 doi "https://doi.org/10.1007/978-981-19-2057-8_12" @default.
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