Artificial intelligence in cardiac telemetry.
Cardiac telemetry has evolved into a vital tool for continuous cardiac monitoring and early detection of cardiac abnormalities. In recent years, artificial intelligence (AI) has become increasingly integrated into cardiac telemetry, making a shift from traditional statistical machine learning models to more advanced deep neural networks. These modern AI models have demonstrated superior accuracy and the ability to detect complex patterns in telemetry data, enhancing real-time monitoring, predictive analytics and personalised cardiac care. In our review, we examine the current state of AI in cardiac telemetry, focusing on deep learning techniques, their clinical applications, the challenges and limitations faced by these models, and potential future directions in this promising field.
Duke Scholars
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Related Subject Headings
- Telemetry
- Neural Networks, Computer
- Machine Learning
- Humans
- Deep Learning
- Cardiovascular System & Hematology
- Artificial Intelligence
- 3202 Clinical sciences
- 3201 Cardiovascular medicine and haematology
- 1103 Clinical Sciences
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Telemetry
- Neural Networks, Computer
- Machine Learning
- Humans
- Deep Learning
- Cardiovascular System & Hematology
- Artificial Intelligence
- 3202 Clinical sciences
- 3201 Cardiovascular medicine and haematology
- 1103 Clinical Sciences