https://doi.org/10.1093/bjrai/ubae008

Introduction to AI in Cardiovascular Imaging

Artificial intelligence (AI) is fundamentally changing cardiovascular imaging, making procedures such as creating cardiac models from CT images and classifying congenital heart disease (CHD) more accurate and efficient. Recent advances have shown the potential of deep learning (DL) and 3D printing in clinical decision-making and treatment planning for CHD.

Ethical Considerations in AI

The increasing use of generative artificial intelligence (GAI) in cardiovascular imaging raises important ethical questions:

•Transparency and Explainability:AI often functions as a “black box,” making it difficult to understand how it makes decisions. This is critical for clinicians’ trust.

•Evaluation Metrics: Tools such as ROC curves*, image quality, clinical relevance, diversity, and human perception studies help evaluate AI performance.

•Automation Bias:The tendency to accept AI results without critical evaluation can lead to over-reliance on automated systems.

•Appropriate Implementation:It is essential to follow ethical principles such as respect for people, beneficence, and justice when using AI.

Health Disparities and Diversity

AI models can be biased if trained on biased datasets. Studies show that image segmentation models based on DL“Deep Learning”.can be less accurate for minority groups. It is, therefore, important to have diversity in the training data.

AI Hallucinations and Legal Ramifications

AI models, such as GPT-3.5 and GPT-4, can create inaccurate information, undermining trust and raising ethical and legal issues. To address this issue, it is necessary to improve training data, incorporate user feedback, and refine models.

Healthcare Data Management

Ensuring data protection and privacy in AI requires strict regulations, ethical governance, and the involvement of trusted third parties to handle sensitive data. Generative models can create plausible patient data, reducing dependency on real patient data.

Continuous Research and Development

Continuous research is essential to address ethical challenges in healthcare data management, improve ethical frameworks, and ensure that AI systems are reliable and effective.

Conclusion

Integrating AI into cardiovascular imaging has great potential, but it requires a balanced approach that takes into account ethical principles, regulations, and ongoing advancements. In this way, the healthcare industry can leverage the benefits of AI while protecting patients’ rights and well-being.

Take notes on the journey…