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Artificial intelligence in endocrinology: Breakthrough technologies and prospects

https://doi.org/10.14341/omet13238

Abstract

In today’s world, characterized by the growing prevalence of endocrine diseases and the complexity of their diagnosis and treatment, AI offers unique opportunities to improve medical care. In the article, we analyze how AI algorithms help detect and classify pathological changes in ultrasound, MRI, CT providing endocrinologists with additional tools for fast and accurate diagnosis. In addition, we are considering the use of AI for big data analysis, including electronic medical records (EHRs), which allows us to develop predictive models and personalize treatment. Special attention is paid to the role of AI in monitoring patients with chronic endocrine diseases, including continuous monitoring of blood glucose levels in diabetes mellitus

This article will be useful for endocrinologists, researchers, students and anyone interested in the use of artificial intelligence in modern medicine.

About the Authors

A. P. Pershina-Miliutina
I.I. Dedov National Medical Research Center of Endocrinology
Russian Federation

Anastasia P. Pershina-Miliutina

Moscow


Competing Interests:

none



M. A. Telegina
A Medclinic
Russian Federation

Maria А. Telegina - ResearcherID: JMB-6130-2023.

Mir Avenue, Building 102, Block 23


Competing Interests:

none



E. V. Еrshova
I.I. Dedov National Medical Research Center of Endocrinology
Russian Federation

Ekaterina V. Ershova - MD, PhD

Moscow


Competing Interests:

none



K. A. Komshilova
I.I. Dedov National Medical Research Center of Endocrinology
Russian Federation

Ksenia A. Komshilova - MD, PhD.

Moscow


Competing Interests:

none



P. A. Еrshova
Lomonosov Moscow State University
Russian Federation

Polina A. Ershova

Moscow


Competing Interests:

none



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Review

For citations:


Pershina-Miliutina A.P., Telegina M.A., Еrshova E.V., Komshilova K.A., Еrshova P.A. Artificial intelligence in endocrinology: Breakthrough technologies and prospects. Obesity and metabolism. 2025;22(2):118-122. (In Russ.) https://doi.org/10.14341/omet13238

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ISSN 2071-8713 (Print)
ISSN 2306-5524 (Online)