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Essentials for AI Research in Cardiology: Challenges and Mitigations
Biyanka Jaltotage1, Girish Dwivedi1,2,3
1Department of Cardiology, Fiona Stanley Hospital, Perth, Western Australia, Australia.
CJC Open
|November 25, 2024
Summary
Artificial intelligence (AI) offers significant benefits for cardiology, but challenges in AI studies need addressing. This review clarifies these challenges and proposes mitigations for safe AI integration in cardiovascular disease management.
Area of Science:
- Cardiology
- Artificial Intelligence
- Medical Technology
Background:
- Artificial intelligence (AI) is rapidly advancing and impacting healthcare, particularly in data-intensive fields like cardiology.
- Cardiovascular disease management faces resource strains, making AI a promising solution.
- AI implementation in clinical care necessitates rigorous evaluation for effectiveness and safety.
Purpose of the Study:
- To assess challenges in conducting studies on AI in cardiovascular disease.
- To explore potential mitigations for successful AI integration.
- To clarify essential components for AI studies in cardiology.
Main Methods:
- Literature review of AI applications in cardiology.
- Analysis of challenges in AI study design and execution.
- Identification of ethical considerations and safety protocols.
Main Results:
- AI offers substantial benefits for cardiovascular disease management.
- Significant challenges exist in AI study design, validation, and ethical implementation.
- Lack of consensus on essential components for AI studies hinders progress.
Conclusions:
- Addressing challenges in AI studies is crucial for safe and effective integration.
- Mitigation strategies are needed to ensure AI tools meet clinical standards.
- Further research and consensus-building are required for AI in cardiology.
