Traditional artificial intelligence (AI) tools have already been implemented in clinical radiology for lesion detection and decision-making. Generative AI (GenAI), comparingly, is a new subset of machine learning that functions based on data probabilities to create content, offering numerous capabilities yet also uncertainties. Multidisciplinary collaboration is essential in safely harnessing the power of GenAI as it transforms medicine. This paper proposes creating a GenAI task force among radiological societies, including the American College of Radiology (ACR), Society of Imaging Informatics in Medicine (SIIM), Radiological Society of North America (RSNA), European Society of Radiology (ESR), Association of University Radiologists (AUR), and American Roentgen Ray Society (ARRS) for its integration into clinical care, health policy, and education. In this paper, we explore how a task force with guidelines will help radiologists and trainees develop essential strategies for integrating evolving AI-related technologies into clinical practice.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11319658 | PMC |
| http://dx.doi.org/10.7759/cureus.64475 | DOI Listing |
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