Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Advances in Science, Engineering and Digital Education, ASEDU 2020

Год издания: 2020

Идентификатор DOI: 10.1088/1742-6596/1691/1/012009

Аннотация: The emergence of big data and artificial intelligence firstly in healthcare has caused considerable excitement, stating the need to improve approaches to diagnosis, prognosis, and treatment. Despite enthusiasm, the methodological assumptions underlying the movement of big data and artificial intelligence in medicine are rarely studied. This article outlines the methodological problems facing this movement. In particular, the following topics were considered: The theory of large data congestion, the limits of the algorithms action, and the phenomenology of the disease. These methodological issues demonstrate several important roles for these technologies that must be considered and studied before they are integrated into the healthcare system. © Published under licence by IOP Publishing Ltd.

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1691, Is. 1

ISSN журнала: 17426588

Издатель: IOP Publishing Ltd

• Mikhailenko O.V. (Siberian Federal University, Prospect Svobodny 79/10, Krasnoyarsk, Russian Federation)
• Dorrer G.A. (Siberian Federal University, Prospect Svobodny 79/10, Krasnoyarsk, Russian Federation, Reshetnev Siberian State University of Science and Technology, prospect Krasnoyarsky rabochy 31, Krasnoyarsk, Russian Federation)

• Scopus
• Ядро РИНЦ (eLIBRARY.RU)