A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains
Sign Up to like & getrecommendations! Published in 2024 at "Engineering with Computers"
DOI: 10.1007/s00366-024-02033-8
Abstract: We propose a novel finite element-based physics-informed operator learning framework that allows for predicting spatiotemporal dynamics governed by partial differential equations (PDEs). The Galerkin discretized weak formulation is employed to incorporate physics into the loss… read more here.
Keywords: operator learning; finite element; geometry; physics ... See more keywords
A machine learning framework to adjust for learning effects in medical device safety evaluation
Sign Up to like & getrecommendations! Published in 2024 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocae273
Abstract: OBJECTIVES Traditional methods for medical device post-market surveillance often fail to accurately account for operator learning effects, leading to biased assessments of device safety. These methods struggle with non-linearity, complex learning curves, and time-varying covariates,… read more here.
Keywords: operator learning; device; device safety; medical device ... See more keywords