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Integrating Artificial Intelligence into Medical Physics Practice: Promises and Ethical Considerations

Makoye John, Rose Mina · American Journal of Artificial Intelligence · 2025

Artificial intelligence (AI) techniques such as deep learning show great potential to enhance medical physics practice by supporting diagnosis, treatment planning, and other clinical tasks. However, responsible integration of AI requires consideration of both promises and ethical risks to ensure technologies are developed and applied safely and for patient benefit. This research review examines opportunities and challenges of integrating AI across various domains of medical physics. Promising applications are discussed such as using large datasets to help radiologists interpret images more accurately and automating routine analyses to increase efficiency. AI may also expand access to care for rural populations through remote services. Potential ethical issues that could hamper responsible integration are also explored. Ensuring AI algorithms avoid human biases that unfairly impact patient outcomes is imperative. Other considerations include responsible oversight structures, ensuring privacy of patient data, and establishing regulatory and quality standards. This review proposes a framework for multidisciplinary collaboration and rigorous testing prior to clinical adoption of AI too

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