How do medical physicists extend quality assurance from machines to algorithms?

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Medical Physicists' Evolving Role in Ensuring AI Algorithm Safety

Medical physicists are extending their traditional quality assurance expertise from physical medical equipment to AI algorithms by applying their established skills in validation, performance evaluation, and risk management. Their existing proficiency in ensuring the safe and accurate operation of devices such as CT scanners and MRI systems is directly transferable to the oversight of AI systems. This transition involves scrutinising algorithms with the same rigour previously applied to hardware, aiming to guarantee that AI tools used in healthcare are reliable, accurate, and fair.
Applying Validation and Quality Assurance Skills to AI

The core competencies of medical physicists, including validation, quality assurance, and risk assessment, are fundamental to overseeing AI in healthcare. These professionals are accustomed to rigorous testing and performance evaluation protocols for medical machinery. In the context of AI, this translates to assessing the performance of algorithms, ensuring their consistency, and identifying potential failure points. Their experience with clinical technology provides a foundational understanding of how these tools integrate into patient care pathways, enabling them to anticipate and mitigate risks associated with AI deployment.
Addressing the Unique Challenges of AI Oversight

Unlike conventional medical devices, AI systems are dynamic and can change over time due to software updates or evolving data inputs. Medical physicists are being tasked with monitoring these changes to ensure continued safety and efficacy. This involves questioning whether an AI system trained on data from one population, such as European or North American patient data, will perform equally well for diverse Malaysian patient demographics. Their role is crucial in identifying potential biases that might arise from such disparities and ensuring the AI's performance remains consistent and reliable in local clinical settings.
Future Roles in AI Governance and Cybersecurity

Looking ahead, the responsibilities of medical physicists are expected to broaden further within the realm of AI in healthcare. Potential future roles include actively monitoring the ongoing performance of AI algorithms post-deployment, detecting and addressing any emerging biases, and contributing to the cybersecurity of these sensitive systems. Furthermore, they are anticipated to participate in hospital AI governance committees, offering their technical expertise to inform policy and ensure that AI adoption aligns with patient safety and welfare, thereby fostering public trust in advanced medical technologies.

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How do medical physicists extend quality assurance from machines to algorithms?

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