Artificial intelligence capabilities for automated diagnosis and prediction of acute stroke outcomes based on magnetic resonance imaging
https://doi.org/10.18705/2782-3806-2025-5-4-330-337
EDN: JMYBTB
Abstract
Acute stroke is one of the leading causes of death and disability worldwide. Millions of people experience this disease every year, with significant consequences for both patients and health systems. Diagnosis and treatment of stroke require fast and accurate decision-making, as time is a critical factor for a successful outcome. However, existing diagnostic methods such as magnetic resonance imaging, although they provide high imaging accuracy, require significant time and human resources. This creates the need to develop new approaches that can improve the effectiveness of diagnosis and prediction of stroke outcomes.
Artificial intelligence is actively developing and finding applications in various fields of medicine, including medical image analysis. The use of artificial intelligence to process MRI data opens up new possibilities for automated diagnosis and prediction of disease outcomes such as stroke. This improves diagnostic accuracy and reduces data analysis time, which is especially important in emergency situations.
About the Authors
R. Kh. AldatovRussian Federation
Aldatov Ruslan Kh., MD, PhD, Head of the Department, Radiologist
Gastello str., 21, Saint Petersburg, 196135
V. A. Fokin
Russian Federation
Fokin Vladimir A., MD, ScD, PhD of the Department of Radiation diagnostics and medical imaging with the clinic
Saint Petersburg
G. E. Trufanov
Russian Federation
Trufanov Gennady E., MD, ScD, PhD, Head of the Department of Radiological Diagnostics and Medical Imaging; Chief Researcher of the Radiology Research Department
Saint Petersburg
M. L. Pospelova
Russian Federation
Pospelova Maria L., MD, ScD, Associate Professor of the Department of Neurology with Clinic, Dean of the Faculty of Pre-University Education and Youth Science of the Institute of Medical Education ; head of the Research Institute of Neuroclinical Oncology of the World-Class Research Centre for Personalized Medicine
Saint Petersburg
A. M. Klimovich
Russian Federation
Klimovich Anastasia M., MD, resident of the Department of Radiation Diagnostics and medical imaging with the clinic
Saint Petersburg
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Review
For citations:
Aldatov R.Kh., Fokin V.A., Trufanov G.E., Pospelova M.L., Klimovich A.M. Artificial intelligence capabilities for automated diagnosis and prediction of acute stroke outcomes based on magnetic resonance imaging. Russian Journal for Personalized Medicine. 2025;5(4):330-337. (In Russ.) https://doi.org/10.18705/2782-3806-2025-5-4-330-337. EDN: JMYBTB














