Infervision

History

2017: Implementation of AI for increase in detectability of tumors

The Chinese company Infervision implements artificial intelligence technologies (AI) and deep training in practice of radiology for the purpose of increase in detectability of tumors at early stages, reports the Medgadget edition on May 17, 2017.

At the heart of Infervision technology — the analysis of tens of thousands x-ray and the KT-researches made in the diagnostic purposes and use of this base for assessment of new pictures. The software developed by Infervision is already applied in a number of health centers of China, and the company states that the accuracy of the received results is very high and close to the conclusion of experienced physicians, in particular, of the deputy chief physician for diagnosis of cardiothoracic diseases in one of the leading Chinese hospitals.

Infervision implements artificial intelligence technology and deep training in practice of radiology for the purpose of increase in detectability of tumors at early stages

Software works with a standard transmission system and storages of medical images of PACS (Picture Archiving and Communication System). For training and a training of the Infervision system about 200 thousand x-rays and data of a computer tomography from medical institutions of the People's Republic of China were used.

The experiment made by specialists of Infervision together with group of radiologists showed that the conclusions made using AI technology were more exact, than at radiologists.

Certainly, the program does not make the diagnosis independently and at all does not replace doctors. More likely, it serves for additional check and identification of the potential centers of a disease and also allows to save physicians from the repeating laborious work, explained in the company.

Infervision hopes that their program will help to reduce time which radiologists spend on studying and processing of pictures of patients, will make diagnostics more exact, operational and will allow to avoid delays at delivery of health care. Also added to the companies that their system continues to samoobuchatsya and be improved in process of receipt in it new data.^[1]

Notes