A team of multi-institutional researchers, including UC San Francisco's Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging (ci2), discussed the current state of radiology through the lens of artificial intelligence (AI) technology.
The researchers, including Matthew Lungren, MD and John Mongan, MD, PhD of the University of California San Francisco and ci2 members, present their findings in "Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts," published in RSNA Radiology.
The authors collected the views from a joint panel, The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society, comprising experts in radiology, medical imaging, and machine learning. Their insights on AI's present and future influence in radiology, and how it is impacted by trust, reproducibility, explainability and accountability, provide a solid foundation for our understanding, the authors write.
Through practical and philosophical discussions, the authors highlight the need of collaboration to improve clinical deployment of AI. These discussions are not just theoretical: they provide strategies and guidelines that radiologists can actively implement in their practice.
Visit the UCSF ci2 blog to read more about research and news.
