Connecting for innovation and equity in global health
PRECISE-AI Proposers’ Day
October 17
The Performance and Reliability Evaluation for Continuous Modifications and Useability of Artificial Intelligence (PRECISE-AI) program aims to develop capabilities that can automatically detect and mitigate AI model degradation and with ARPA-H, will bring together machine learning experts, health information specialists, and clinicians to address five technical areas.
TA 1 focuses on the automatic extraction and integration of data across different clinical use cases to establish a “ground truth” about each patient. TA 2 seeks to continuously monitor model performance, determine root causes of degradation, and suggest or make automatic corrections when needed. TA 3 aims to quantify uncertainty and improve clinical outcomes by finding novel ways of communicating model uncertainty and complementary measures to clinicians, developers, and other stakeholders. TA 4 will aggregate and share data across medical institutions and across performers to advance development of TA 1-3. TA 5 will confirm the progress made by all the TAs by performing independent verification and validation.