Notice ID: ARPA-H-SOL-25-113
Related Notice: ARPA-H-SOL-25-113
The rapid advancement of artificial intelligence (AI) technologies is transforming healthcare by improving efficiencies, reducing costs, and enhancing health outcomes. This potential is evident with over 850 FDA-approved medical devices now incorporating AI functionalities, a tenfold increase from 2018 to 2023. However, the ability to ensure the ongoing safety and efficacy of these AI systems has not kept pace.
The PRECISE-AI program is soliciting proposals to create novel self-correction techniques that optimally maintain the peak performance of clinical AI decision support tools, both when operating independently and in combination with the clinicians who use them. PRECISE-AI aspires to create a future where predictive AI models continuously communicate with clinicians in a way that appropriately earns the clinician’s trust. Proposers should address critical challenges in the ability of AI-DSTs to actively monitor and maintain their optimal performance with consideration to local health systems, operational processes such as data acquisition, and patient characteristics, after their commercial deployment …
PRECISE-AI performers will create an open-source repository of tools that enable continuous monitoring and auto-correction of AI-DST. Proposers should focus specifically on AI-DSTs that make a diagnosis or prediction that is later validated by another test or clinical action. By automatically extracting surrogate ground truth label information from health records, automated monitoring techniques can continuously evaluate when AI decision support tools make accurate diagnoses and …
PRECISE-AI seeks novel proposals to analyze the monitoring data to suggest root causes for performance deterioration. The root cause analysis will be used to recommend self-corrective actions that enable the AI model to improve its performance. When performance degradation occurs, it will be important to communicate the heightened risk of medical errors to clinicians, the developers of the AI decision support tool, hospital administrators, and …
PRECISE-AI aims to improve the performance of clinicians that use AI-DSTs. Once the AI-DST monitoring and auto-correction tools are developed, it will be necessary to help transform these into meaningful insights for clinicians that enhance patient care. Proposers are encouraged to innovate new methods and tools for improving the transparency, interpretability, and actionability of AI model outputs to …
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