The ACR Data Science Institute and AI Advisory Group: Harnessing the Power of Artificial Intelligence to Improve Patient Care.
J Am Coll Radiol. 2018 Mar;15(3 Pt B):577-579. doi: 10.1016/j.jacr.2017.12.024. Epub 2018 Feb 3. McGinty GB1, Allen B Jr.2.
In the ubiquitous media coverage of artificial intelligence (AI) and machine learning, radiology has emerged as the poster child for professions that will potentially be rendered obsolete by indefatigable robots who never miss an out-of-place pixel and whose hierarchy of needs includes nothing more than a regular software update and a reliable power source. Although this dystopian vision of radiology’s future is far from accurate, a trusted advocate for our patients and our profession is needed to ensure that AI and other advanced technologies are used appropriately and that they deliver what they promise to enhance medical care and outcomes. Radiology specialty societies can advance AI in ways that allow radiology professionals to increase the value we provide to our patients and enhance our role in our health systems. Specialty societies can focus educational efforts for radiologists and all stakeholders on how radiologists can integrate AI into clinical practice. Our specialty societies such as the ARRS and the RSNA, and the subspecialty societies, will play a key role in educating radiologists about how AI will augment our practices in the future. Specialty societies will also have a role in developing the AI use cases that will allow AI to augment, not replace, the care radiologists provide. The RSNA, through its Radiology Informatics Committee, has been a leader in developing a lexicon of radiological terminology (RadLex)  and in aggregating structured reporting templates through its Radiology Reporting Initiative . These areas represent additional opportunities for radiologists to incorporate data elements used in AI into a Common Data Elements lexicon and structured reporting tools that will collect the output for AI algorithms into reporting tools. The RSNA also hosted a competition for AI developers around a Pediatric Bone Age Determination use case at RSNA 2017. Finally, the ACR has a long history of developing relationships with government regulators including the FDA and has created a number of informatics tools and frameworks for integrating clinical recommendations into our radiology reports [3,4]. The ACR can leverage these relationships and tools into initiatives that will facilitate the implementation of AI into clinical practice that will augment the value radiologists provide to our patients.