GAO’s study titled Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning (ML) Technologies for Medical Diagnostics looks at how artificial intelligence (AI) has emerged as a tool for solving complex problems in the area of medical diagnostics.
To do the study, GAO assessed available and emerging ML technologies, interviewed stakeholders from government, industry, and academia, convened a meeting of experts in collaboration with the National Academy of Medicine, and reviewed reports and scientific literature.
GAO’s study reports that several ML technologies a subfield of AI, are available in the U.S to assist with the diagnostic process. Benefits include earlier detection of diseases, more consistent analysis of medical data, and increased access to care particularly for underserved populations.
The study identifies a variety of ML-based technologies for five selected diseases such as certain cancers, diabetic retinopathy, Alzheimer’s disease, heart disease, and COVID-19. Most technologies rely on data from imaging such as x-rays, or magnetic resonance imaging (MRI). However, ML technologies have generally not been widely adopted.
However, the study examines the challenges to the development and use of ML technologies in medical diagnostics to include:
- Demonstrating real world performance across diverse clinical settings and in rigorous studies,
- Developing technologies that integrate into clinical workflows
- Addressing regulatory gaps in order to raise technological, economic and regulatory questions
GAO found the benefits for using ML technologies includes earlier detection of diseases, more consistent analysis of medical data, and increased access to care particularly for underserved populations.
Go to https://gao.gov/products/gao-22-104629 for the report “ARTIFICIAL INTELLIGENCE IN HEALTHCARE: Benefits and Challenges of Machine Learning Technologies for Medical Diagnostics.”
For more information, email howardk@gao.gov or call Karen L. Howard at (202) 512-6888.