Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study
Sign Up to like & getrecommendations! Published in 2024 at "Empirical Software Engineering"
DOI: 10.1007/s10664-024-10515-y
Abstract: Graph Neural Networks (GNNs) have gained prominence in various domains, such as social network analysis, recommendation systems, and drug discovery, due to their ability to model complex relationships in graph-structured data. GNNs can exhibit incorrect… read more here.
Keywords: empirical study; selection methods; test; selection ... See more keywords
Data-Driven Optimal Test Selection Design for Fault Detection and Isolation Based on CCVKL Method and PSO
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3168930
Abstract: Accurate fault detection and isolation (FDI) relies on the information collection. This can be done by the optimal test selection which can also reduce the life cost of engineering systems. In recent years, some researchers… read more here.
Keywords: optimal test; test selection; test; fault ... See more keywords
Detecting patients with Cushing's syndrome: The importance of initial test selection.
Sign Up to like & getrecommendations! Published in 2022 at "Australian journal of general practice"
DOI: 10.31128/ajgp-09-21-6178
Abstract: BACKGROUND AND OBJECTIVES The recommended initial tests for suspected Cushing's syndrome are late-night salivary cortisol (LNSC), 24-hour urinary free cortisol (UFC) and the 1 mg overnight dexamethasone suppression test (ONDST). These tests have higher sensitivity and… read more here.
Keywords: test selection; test; cortisol; cushing syndrome ... See more keywords