| DC Field | Value | Language |
|---|
| dc.contributor.author | Xudoyberganova Noila Hamitovna Lecturerat the Departmentof Propedeuticsof Internal DiseasesNo.2 Tashkent state medical university Davronova Iroda Jasurjon kizi Student of Tashkent State Medical University | - |
| dc.date.accessioned | 2026-03-25T05:22:50Z | - |
| dc.date.available | 2026-03-25T05:22:50Z | - |
| dc.date.issued | 2026-03-13 | - |
| dc.identifier.uri | http://repo.tma.uz/xmlui/handle/1/3167 | - |
| dc.description.abstract | This paper explores the transformative potential and clinical hurdles of integrating Artificial Intelligence (AI) into the management of cardiomyopathies. While neural networks demonstrate remarkable precision in analyzing echocardiographic patterns and cardiac MRI, their transition from laboratory settings to bedside practice remains complex. We examine the "black box" phenomenon − where algorithmic logic remains opaque to clinicians − and the ethical imperatives of automated decision-making. By synthesizing recent breakthroughs with the practicalities of digital cardiology, this study argues for a hybrid model where AI functions as a sophisticated clinical partner rather than a diagnostic replacement, specifically bridging the gap between standardized protocols and personalized patient care. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | cardiomyopathy, artificial intelligence, neural networks, cardiac. imaging, MRI, digital cardiology, precision medicine. Introduction | en_US |
| dc.title | THEORETICAL AND SCIENTIFIC FOUNDATIONS FOR USAGE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN DIAGNOSING AND TREATING CARDIOMYOPATHIES. | en_US |
| dc.title.alternative | London International Monthly Conference on Multidisciplinary Research and Innovation WORLD SCIENCE PUBLISHING LTD, LONDON, MARCH, 2026 | en_US |
| dc.type | Article | en_US |
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