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The Tomsk oncology dispensary implemented a neuronet on diagnosis of breast cancer

Customers: Tomsk regional oncological clinic

Contractors: Sberbank


Project date: 2020/11

As it became known on November 9, 2020, the Tomsk regional oncological clinic implemented a neuronet on diagnosis of breast cancer. The used artificial intelligence is a development of Sber, says the company.

The Tomsk oncology dispensary began to use AI model for the analysis and processing of mammographic pictures according to the results of the successful pilot project starting several months before. After project implementation process of the analysis of mammograms using artificial intelligence in medical institution became completely automated and synchronized with diagnostic devices of a medical institution.

The Tomsk oncology dispensary began to use a neuronet for diagnosis of breast cancer

The neuronet which is the cornerstone of AI model estimates images literally "on the fly": the picture is processed within several seconds, and in case of probable pathology the doctor receives assessment of the picture from a system and more carefully studies and describes it.

Specialists of oncology dispensary note that image processing using AI technologies considerably accelerated work of doctors and allowed to send patients to a biopsy and other additional inspections in day of carrying out mammography.

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The test showed that the machine estimates pictures not worse than doctors, – the manager of department of radiodiagnosis of the Tomsk regional oncological clinic Evgeny Karpov says. – Literally for several seconds after processing the doctor receives picture assessment from a system in coded form and considers it as the second opinion. Daily artificial intelligence selects on average 7-8 patients who should be sent for additional inspection.
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According to the first deputy chairman of Sberbank Alexander Vedyakhin, the main advantage of our AI model — capability quickly to process a large number of images. It saves time not only of doctors, but also patients — they begin to receive the necessary treatment quicker that eventually saves health and saves lives.[1]

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