In the past 10 years, artificial intelligence (AI) applications have exploded in numerous fields, including medicine. Myriad publications report that the use of AI in health care is increasing, and AI has shown utility in many medical specialties, eg, pathology, radiology, and oncology.1,2
In cancer pathology, AI was able not only to detect various cancers, but also to subtype and grade them. In addition, AI could predict survival, the success of therapeutic response, and underlying mutations from histopathologic images.3 In other medical fields, AI applications are as notable. For example, in imaging specialties like radiology, ophthalmology, dermatology, and gastroenterology, AI is being used for image recognition, enhancement, and segmentation. In addition, AI is beneficial for predicting disease progression, survival, and response to therapy in other medical specialties. Finally, AI may help with administrative tasks like scheduling.
However, many obstacles to successfully implementing AI programs in the clinical setting exist, including clinical data limitations and ethical use of data, trust in the AI models, regulatory barriers, and lack of clinical buy-in due to insufficient basic AI understanding.2 To address these barriers to successful clinical AI implementation, we decided to create a formal governing body at James A. Haley Veterans’ Hospital in Tampa, Florida. Accordingly, the hospital AI committee charter was officially approved on July 22, 2021. Our model could be used by both US Department of Veterans Affairs (VA) and non-VA hospitals throughout the country.
AI Committee
The vision of the AI committee is to improve outcomes and experiences for our veterans by developing trustworthy AI capabilities to support the VA mission. The mission is to build robust capacity in AI to create and apply innovative AI solutions and transform the VA by facilitating a learning environment that supports the delivery of world-class benefits and services to our veterans. Our vision and mission are aligned with the VA National AI Institute. 4
The AI Committee comprises 7 subcommittees: ethics, AI clinical product evaluation, education, data sharing and acquisition, research, 3D printing, and improvement and innovation. The role of the ethics subcommittee is to ensure the ethical and equitable implementation of clinical AI. We created the ethics subcommittee guidelines based on the World Health Organization ethics and governance of AI for health documents.5 They include 6 basic principles: protecting human autonomy; promoting human well-being and safety and the public interest; ensuring transparency, explainability, and intelligibility; fostering responsibility and accountability; ensuring inclusiveness and equity; and promoting AI that is responsive and sustainable (Table 1).
As the name indicates, the role of the AI clinical product evaluation subcommittee is to evaluate commercially available clinical AI products. More than 400 US Food and Drug Administration–approved AI medical applications exist, and the list is growing rapidly. Most AI applications are in medical imaging like radiology, dermatology, ophthalmology, and pathology.6,7 Each clinical product is evaluated according to 6 principles: relevance, usability, risks, regulatory, technical requirements, and financial (Table 2).8 We are in the process of evaluating a few commercial AI algorithms for pathology and radiology, using these 6 principles.