The assessment of each new image enables the system to self-improve, with researchers relying on the supercomputer center, Polytechnic, to speed up learning and testing processes. They plan to reduce diagnostic testing time per patient from 20 to 2 seconds in the future by transferring images to the supercomputer using the internet, with the radiologist receiving the marked image, rather than the large CT image. This decreases time for analysis and diagnostics.

"The system is not only an artificial intelligence system, it is a whole digital platform. Using the cloud service every clinic will be able to connect to the platform to analyze the CT of their patients," said Utkin. "This data will be transferred to supercomputer "Polytechnic". So the hospitals don't need to install the specific software, but just to connect the digital platform.".


The researchers plan to increase the number of images by four times by mid-2019 and at some point in the future, will adapt the system to assess results of ultrasound and X-ray in the evaluation of other organs.

Open testing of the system will take place at the beginning of 2019, with the system first used at the St. Petersburg Clinical Research Center for Specialized Types of Medical Care (Oncological) and eventually extended to other institutions.

The research team consisted of staff from Peter the Great St. Petersburg Polytechnic University (SPbPU) and the Russian Academic Excellence Initiative participant, and radiologists from St. Petersburg Clinical Research for Specialized Types of Medical Care (Oncological).

The project was supported by the Russian Science Foundation.

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