التفاصيل البيبلوغرافية
| العنوان: |
How Machine Learning Might Help Improve Cardiac Imaging. |
| المؤلفون: |
Anderer S, Hswen Y |
| المصدر: |
JAMA [JAMA] 2024 Mar 26; Vol. 331 (12), pp. 995-997. |
| نوع المنشور: |
Journal Article |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: American Medical Association Country of Publication: United States NLM ID: 7501160 Publication Model: Print Cited Medium: Internet ISSN: 1538-3598 (Electronic) Linking ISSN: 00987484 NLM ISO Abbreviation: JAMA Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: Chicago : American Medical Association, 1960- |
| مواضيع طبية MeSH: |
Machine Learning* , Cardiac Imaging Techniques*/methods, Diagnostic Imaging |
| فهرسة مساهمة: |
Local Abstract: [plain-language-summary] In this Medical News interview, University of California, San Francisco, cardiologist Rima Arnaout, joins JAMA Editor in Chief Kirsten Bibbins-Domingo to discuss the transformative potential of AI on cardiac imaging. |
| تواريخ الأحداث: |
Date Created: 20240306 Date Completed: 20240327 Latest Revision: 20240329 |
| رمز التحديث: |
20240329 |
| DOI: |
10.1001/jama.2023.23070 |
| PMID: |
38446469 |
| قاعدة البيانات: |
MEDLINE |
