The joint research team of the Japan Institute of Physical Chemistry and the National Cancer Research Center of Japan has established a method for automatic detection of early gastric cancer with high precision using an artificial intelligence (AI) system constructed from a small number of confirmed data, thereby reducing the missed diagnosis of gastric cancer and is expected to be realized. Early detection, early treatment.
The R&D team randomly selected about 10,000 areas that definitely contained the "cancer part" and the "normal part" from about 100 images of early gastric cancer and about 100 normal tissues. A total of about 20,000 images were obtained. And use data expansion technology to expand to about 360,000 images for re-learning.
The research team verified whether the AI ​​can accurately judge these images after re-learning. The results showed that the detection sensitivity was 80.0% and the specificity was 94.8%. In addition, the positive coincidence rate was 93.4%, and the negative coincidence rate was 83.6%. The time required to process an image is only 4 milliseconds, which will be used in clinical applications in the future, which is sufficient for real-time automatic detection. (Source of this column: Japan Science and Technology Promotion Agency: Chen Hao, reporter of the newspaper in Japan)
Source: Technology Daily
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