The Identification of Latent Atrial Fibrillation, Decreased Ejection Fraction of the Left Ventricle and Potassium Metabolism Disorders on the Conventional Electrocardiogram Using Deep Convolutional Neural Network as an Element of Artificial Intelligence

Мазаев, В.П.; Komkov, A.A.; Ryazanova, S.V.; Samochatov, D.N.; Драпкина, О. М.

doi:10.17513/spno.30478

Cited by 1 publication

(1 citation statement)

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“…В настоящее время технологические возможности создания СПКР используют многие системы накопления и обработки данных с применением алгоритмов машинного обучения и свёрточных нейронных сетей, что приводит к получению данных, опережающих способности человеческого мышления принять логику рекомендуемых решений [29].…”

Section: обсуждение проблем использования спкрunclassified

Effective decision support systems in clinical practice and prevention: literature review

Komkov,

Ryazanova,

Mazaev

2023

CardioSomatics

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Clinical decision support systems (CDSS) often outperform human capabilities for processing a large amount of information, dramatically simplifying the work of specialists and avoiding medical errors. The implementation of such systems is a complex task that requires high-tech developments. The annual increase in the development of such systems has a geometric progression. However, it is unclear if most of them will be integrated into clinical practice and recommendations. The use of CDSS to address various disease diagnosis, treatment, and prevention issues is demonstrated, and possible linkages between scientific clinical observations and CDSS are examined. Currently, many data gathering and processing systems use machine learning algorithms and convolutional technologies to create CDSS, resulting in data that exceeds the ability of human thinking to determine the logic of recommended decisions. This study presents the most studied modern CDSS, the possibilities of their application, and the implementation issues.

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Section: обсуждение проблем использования спкрunclassified