Artificial Intelligence in Enhancing Syncope Management - An Update
This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratification, syncope poses significant healthcare challenges. AI has the potential to improve symptom differentiation, risk assessment, and patient management. Machine learning, specifically Artificial Neural Networks, has shown promise in accurate risk stratification. AI-powered clinical decision support tools can improve patient evaluation and resource utilization. While AI holds great promise for syncope management, challenges such as data quality, class imbalance, and defining risk categories remain. Ethical concerns about patient privacy, as well as the need for human empathy, complicate AI integration. Collaboration among data scientists, clinicians, and ethics experts is critical for the successful implementation of AI, which has the potential to improve patient outcomes and healthcare efficiency in syncope management.
Other Information
Published in: Current Problems in Cardiology
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://doi.org/10.1016/j.cpcardiol.2023.102079
Funding
Open Access funding provided by the Qatar National Library
History
Language
- English
Publisher
ElsevierPublication Year
- 2024
License statement
This Item is licensed under the Creative Commons Attribution 4.0 International LicenseInstitution affiliated with
- Hamad Medical Corporation