WASHINGTON – Scientists at Google have claimed that an Artificial Intelligence model developed by them is more effective than human experts in detecting the lung cancer. The AI-based system uses Deep Learning to detect malignant lung nodules on LDCT (low-dose chest computed tomography) scans. This would help to ensure the early diagnosis of lung cancer and hence, it will be possible to treat the disease in its earlier stage. An automated image evaluation system would help to enhance the accuracy in the early diagnosis of the deadly disease. While comparing the results with that of radiologists, it was found that the deep-learning based system works better than those radiologists.
Deep-learning technique uses 3D images. But radiologists carry out the diagnosis of lungs by detecting thousands of 2D images. Hence, it makes the whole process easier to detect any tumor with the help of 3D images.
A research assistant professor at Northwestern University in the United States, Mozziyar Etemadi, shared, “AI in 3D can be much more sensitive in its ability to detect early lung cancer than the human eye looking at 2D images. This is technically ‘4D’ because it is not only looking at one CT scan, but two over time. In order to build the AI to view the CTs in this way, you require an enormous computer system of Google-scale. The concept is novel but the actual engineering of it is also novel because of the scale.”
The research highlights the importance of AI-based technology, as it would make the entire screening process a lot easier if executed well. Hence, by early detection of lung cancer, it will be possible to reduce the mortality rate as lung cancer contributes to the highest number of deaths.
In the Deep-learning technology, both primary CT scan as well as prior CT scan results are taken into consideration. This makes it feasible to predict lung-cancer malignancy risk and hence detect the lung cancer in its earlier stage. The new AI-based system has been tested for over 6,000 de-identified CT scan sets in order to study its accuracy. And, it was found that this system helps to spot minuscule malignant nodules easily.
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