Artificial Intelligence in Cardiac Imaging
Machine learning (ML), a subset of artificial intelligence, shows promising results in cardiology, especially in cardiac Imaging. ML algorithms allow cardiologists to explore new possibilities and make detection less obvious. This provides new opportunities to improve patient care and open new doors for medical decision-making. This review highlights the role of Machine learning in cardiac imaging for the accuracy of phenotyping and predicting heart failure.
- Computer-aided diagnosis
- Clinical decision support
- Computer-aided detection
- Quantitative analysis tools
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Artificial Intelligence in Cardiac Imaging Conference Speakers
Recommended Sessions
- Artificial Intelligence in Cardiac Imaging
- CABG(Coronary artery bypass grafting) Surgery
- Cardiac Disorder
- Cardiac Magnetic Resonance Imaging(MRI)
- Cardiac Medication and Devices
- Cardiac Pharmacotherapy
- Cardiac Rehabilitation
- Cardiac Stress Testing
- Cardio Geriatrics
- Cardio-Oncology
- Clinical Case Report on Cardiology
- Congenital Heart Defect
- Diagnostic test in Cardiology
- Echocardiography
- Innovations in Cardiac Imaging / Multimodality Imaging
- Interventional Cardiology
- Nuclear Cardiology
- Obesity and Heart
- Pediatric Cardiology
- Sports Cardiology
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