Artificial Intelligence Survey for 2020 by ACR Data Science Institute

An Outside of the healthcare industry, commercially available artificial
intelligence (AI) algorithms have shown signs of racial, gender, and societal prejudice.
The development of AI algorithms in the fields of radiologic sciences and healthcare is
significantly impacted by these biases. The physician community should work with
developers and regulators to create paths that guarantee algorithms sold for widespread
clinical practice are secure, efficient, and free of unintended bias in order to prevent the
introduction of bias in healthcare AI. Structured AI use cases with data elements have
been developed by the ACR Data Science Institute to make it easier to create standardized
datasets for AI testing and training at various universities. This project seeks to encourage
the accessibility of a variety of data for algorithm development. Additionally, ACR
Certify-AI and ACR Assess-AI, validation and monitoring services offered by the ACR
Data Science Institute, integrate guidelines for minimizing algorithm bias and advancing
health fairness.


The ACR should support pricing methods for AI that guarantee access to AI
technologies for all patients, regardless of their socioeconomic level or the resources
available within their healthcare systems, in addition to promoting diversity. The ACR
Data Science Institute conducted its first annual survey of ACR members to better
understand how artificial intelligence (AI) is used in clinical practice and to create a
baseline for tracking trends. Participants were asked to answer questions about their
practice's demographics and to say whether or not they presently use AI in their clinical
work, as well as in what capacity. AI has started to be used in mammography screening
procedures. According to the report, larger practices were more likely to use AI than
smaller ones. The majority of individuals who used AI in clinical practice did so to
improve interpretation; the most frequent uses were for the early detection of cerebral
hemorrhage, pulmonary emboli, and abnormalities in mammograms. According to the
survey results, clinical practice has just recently begun to incorporate AI at a moderate
rate. The data acquired from the poll will help researchers and business experts create AI
solutions that can improve radiological practice, resulting in enhancements to the
effectiveness and quality of patient care.