HealthLeaders Media October 10, 2022
Adaptive techniques could improve diagnostic effectiveness in five key disease areas, a Government Accountability Office report states, but only if the data is high quality.
Low-quality data is hampering artificial intelligence (AI) and machine learning (ML) from making more inroads in healthcare diagnostics, according to a new report from the US Government Accountability Office (GAO).
In addition, the report found, these technologies are yet to fully demonstrate real-world performance in diverse clinical settings.
“Our policy options–like improving data access and collaboration–may help address the challenges,” the report stated.
Potential benefits of machine learning in the diagnostic process include earlier detection of diseases, more consistent analysis of medical data, and increased access to care, particularly among underserved populations, the report said.
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