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ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 38 Issue 1
Jan.  2022
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Article Contents

Application and prospect of deep learning in primary liver cancer-related diagnostic model

DOI: 10.3969/j.issn.1001-5256.2022.01.003
Research funding:

Science and Technology Innovation Platform Project of Fuzhou Science and Technology Bureau (2021-P-055);

Specific Foundation of Development and Reform Commission in Fujian Province (31010308)

  • Received Date: 2021-10-14
  • Accepted Date: 2021-10-17
  • Published Date: 2022-01-20
  • Deep learning is a process in which machine learning obtains new knowledge and skills by simulating the learning behavior of human brain through massive data training and analysis. With the development of medical technology, a large amount of data has been accumulated in the medical field, and the research on data may help to understand the relationships and rules within data and predict the onset and prognosis of human diseases. Deep learning can find the hidden information in data and has been increasingly used in the medical field. Primary liver cancer is a malignant tumor with high incidence and mortality rates, poor prognosis, and a high recurrence rate, and early diagnosis, timely treatment, and prediction of recurrence have always been the research hotspots in recent years. This article reviews the advances in the application of deep learning in the diagnosis and recurrence of liver cancer from the aspects of risk prediction, postoperative recurrence, and survival risk prediction.

     

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