Artificial intelligence in diabetology

This review presents the applications of artificial intelligence for the study of the mechanisms of diabetes development and generation of new technologies of its prevention, monitoring and treatment. In recent years, a huge amount of molecular data has been accumulated, revealing the pathogenic mec...

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Autores principales:	V. V. Klimontov, V. B. Berikov, O. V. Saik
Formato:	article
Lenguaje:	EN RU
Publicado:	Endocrinology Research Centre 2021
Materias:	diabetes artificial intelligence machine learning data mining text mining gene networks decision support systems Nutritional diseases. Deficiency diseases RC620-627
Acceso en línea:	https://doaj.org/article/45abd41212fd4b61bbeb47a926e6e956
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spelling	oai:doaj.org-article:45abd41212fd4b61bbeb47a926e6e9562021-11-14T09:00:23ZArtificial intelligence in diabetology2072-03512072-037810.14341/DM12665https://doaj.org/article/45abd41212fd4b61bbeb47a926e6e9562021-07-01T00:00:00Zhttps://www.dia-endojournals.ru/jour/article/view/12665https://doaj.org/toc/2072-0351https://doaj.org/toc/2072-0378This review presents the applications of artificial intelligence for the study of the mechanisms of diabetes development and generation of new technologies of its prevention, monitoring and treatment. In recent years, a huge amount of molecular data has been accumulated, revealing the pathogenic mechanisms of diabetes and its complications. Data mining and text mining open up new possibilities for processing this information. Analysis of gene networks makes it possible to identify molecular interactions that are important for the development of diabetes and its complications, as well as to identify new targeted molecules. Based on the big data analysis and machine learning, new platforms have been created for prediction and screening of diabetes, diabetic retinopathy, chronic kidney disease, and cardiovascular disease. Machine learning algorithms are applied for personalized prediction of glucose trends, in the closed-loop insulin delivery systems and decision support systems for lifestyle modification and diabetes treatment. The use of artificial intelligence for the analysis of large databases, registers, and real-world evidence studies seems to be promising. The introduction of artificial intelligence systems is in line with global trends in modern medicine, including the transition to digital and distant technologies, personification of treatment, high-precision forecasting and patient-centered care. There is an urgent need for further research in this field, with an assessment of the clinical effectiveness and economic feasibility.V. V. KlimontovV. B. BerikovO. V. SaikEndocrinology Research Centrearticlediabetesartificial intelligencemachine learningdata miningtext mininggene networksdecision support systemsNutritional diseases. Deficiency diseasesRC620-627ENRUСахарный диабет, Vol 24, Iss 2, Pp 156-166 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU
topic	diabetes artificial intelligence machine learning data mining text mining gene networks decision support systems Nutritional diseases. Deficiency diseases RC620-627
spellingShingle	diabetes artificial intelligence machine learning data mining text mining gene networks decision support systems Nutritional diseases. Deficiency diseases RC620-627 V. V. Klimontov V. B. Berikov O. V. Saik Artificial intelligence in diabetology
description	This review presents the applications of artificial intelligence for the study of the mechanisms of diabetes development and generation of new technologies of its prevention, monitoring and treatment. In recent years, a huge amount of molecular data has been accumulated, revealing the pathogenic mechanisms of diabetes and its complications. Data mining and text mining open up new possibilities for processing this information. Analysis of gene networks makes it possible to identify molecular interactions that are important for the development of diabetes and its complications, as well as to identify new targeted molecules. Based on the big data analysis and machine learning, new platforms have been created for prediction and screening of diabetes, diabetic retinopathy, chronic kidney disease, and cardiovascular disease. Machine learning algorithms are applied for personalized prediction of glucose trends, in the closed-loop insulin delivery systems and decision support systems for lifestyle modification and diabetes treatment. The use of artificial intelligence for the analysis of large databases, registers, and real-world evidence studies seems to be promising. The introduction of artificial intelligence systems is in line with global trends in modern medicine, including the transition to digital and distant technologies, personification of treatment, high-precision forecasting and patient-centered care. There is an urgent need for further research in this field, with an assessment of the clinical effectiveness and economic feasibility.
format	article
author	V. V. Klimontov V. B. Berikov O. V. Saik
author_facet	V. V. Klimontov V. B. Berikov O. V. Saik
author_sort	V. V. Klimontov
title	Artificial intelligence in diabetology
title_short	Artificial intelligence in diabetology
title_full	Artificial intelligence in diabetology
title_fullStr	Artificial intelligence in diabetology
title_full_unstemmed	Artificial intelligence in diabetology
title_sort	artificial intelligence in diabetology
publisher	Endocrinology Research Centre
publishDate	2021
url	https://doaj.org/article/45abd41212fd4b61bbeb47a926e6e956
work_keys_str_mv	AT vvklimontov artificialintelligenceindiabetology AT vbberikov artificialintelligenceindiabetology AT ovsaik artificialintelligenceindiabetology
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Artificial intelligence in diabetology

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