Implementation of artificial intelligence technologies in various fields of modern medicine

Автор: Skalozub D.V., Minasyan D.S., Antonyuk A.G., Lashevich S.A., Reznikova M.A.

Журнал: Международный журнал гуманитарных и естественных наук @intjournal

Рубрика: Медицинские науки

Статья в выпуске: 12-4 (87), 2023 года.

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This article explores the impact of artificial intelligence (AI) on everyday life and its potential in the field of medicine. Surveys indicate that an increasing number of people are encountering AI in various areas, such as wearable devices, chatbots, and personalized recommendations. In medicine, AI has a revolutionary potential, influencing diagnosis, treatment selection, drug development, and disease prevention. This article focuses on the implementation of AI in medicine through the use of an automated questionnaire for early diagnosis of COVID-19. Developers have created a system using algorithms and decision rules to assess the presence of COVID-19 or potential virus infection. The overall sensitivity of the methodology is 89.5%. The article also discusses the application of AI in genomics of cancerous tumors for more precise classification and prognosis. Machine learning and AI enable the identification of molecular markers and evaluation of gene expression with different mutations, significantly improving diagnostic accuracy and prognosis of oncological conditions. Additionally, the article covers the use of AI in vertebral medicine (vertebrology) and predicting pre-eclampsia. Research is being conducted to employ AI for preoperative assessment, planning, and support in spine surgeries. In the field of pre-eclampsia prediction, researchers are developing models based on biophysical factors, biochemical markers, and AI algorithms. The findings suggest the potential of AI in diagnosing COVID-19, genomics of tumors, vertebral medicine, and predicting pre-eclampsia.

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Artificial intelligence, medicine, diagnosis, vertebral medicine, pre-eclampsia

Короткий адрес: https://sciup.org/170201635

IDR: 170201635   |   DOI: 10.24412/2500-1000-2023-12-4-23-26

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