Search papers, labs, and topics across Lattice.
College of Health Solutions, Arizona State University, Phoenix, AZ, USA
3
0
5
Trust in AI for digital health hinges on robust and explainable systems, yet this review reveals significant gaps in current approaches that must be addressed.
Task-agnostic adapter selection without trainable parameters leads to state-of-the-art continual learning performance with minimal forgetting.
Personalized meal recommendations can now effectively prevent postprandial hyperglycemia by leveraging counterfactual explanations and real-time data integration.
