Trustworthy Artificial Intelligence in Medical Imaging.

Area of Science:

• Medical Artificial Intelligence
• AI Ethics
• Computer Science

Background:

• Societal trust and the development of trustworthy artificial intelligence (AI) systems are paramount for AI's progress and implementation in medicine.
• The increasing integration of AI in diverse medical and imaging applications necessitates the establishment of dependable and reliable AI systems.

Purpose of the Study:

• To identify and discuss fourteen core principles essential for developing trustworthy AI in the medical field.
• To guide the creation of AI systems that are accurate, resilient, fair, explainable, safe, and transparent.

Main Methods:

• Review and synthesis of existing literature and best practices in AI ethics and development.
• Identification of key attributes contributing to trustworthy AI in a medical context.

Main Results:

• The article proposes fourteen core principles as a framework for trustworthy AI development.
• These principles address critical aspects such as accuracy, resilience, fairness, explainability, safety, and transparency.

Conclusions:

• Adherence to these fourteen principles is vital for fostering societal trust in medical AI.
• Implementing these guidelines will facilitate the responsible and effective deployment of AI technologies in healthcare.