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http://repo.tma.uz/xmlui/handle/1/4781Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ruziyeva, Sitora | - |
| dc.date.accessioned | 2026-07-09T10:58:54Z | - |
| dc.date.available | 2026-07-09T10:58:54Z | - |
| dc.date.issued | 2024-07-19 | - |
| dc.identifier.uri | http://repo.tma.uz/xmlui/handle/1/4781 | - |
| dc.description.abstract | This thesis explores the advancements in artificial intelligence (AI) with a specific focus on its role in diagnosing fractures in facial trauma imaging. The capabilities of AI algorithms, particularly in machine learning and deep learning, are scrutinized to determine their effectiveness and reliability in comparison with traditional diagnostic methods. The goal is to provide a comprehensive review that justifies the integration of AI into clinical practice for enhancing diagnostic accuracy and patient outcomes in facial trauma scenarios. | en_US |
| dc.language.iso | en | en_US |
| dc.title | Application of Artificial Intelligence in the Diagnosis of Facial Trauma Imaging | en_US |
| dc.type | Thesis | en_US |
| Appears in Collections: | Articles | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Application of Artificial Intelligence in the Diagnosis of Facial Trauma Imaging.pdf | 1.3 MB | Adobe PDF | View/Open |
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