Title
Neural network performance metrics for biomedical applications
Abstract
Neural network performance measurements are discussed. Included are percent correct, average sum-squared error, receiver operating characteristics (ROC) curve measurements, other measurements based on ROC curve parameters, and the chi-square goodness-of-fit metric. The specific measure chosen depends on the type of system and other more loosely defined parameters such as the level of technical sophistication of the system end user
Year
DOI
Venue
1990
10.1109/CBMSYS.1990.109410
Chapel Hill, NC
Keywords
Field
DocType
medical computing,neural nets,ROC curve parameters,average sum-squared error,biomedical applications,chi-square goodness-of-fit metric,percent correct,receiver operating characteristics
Data mining,Receiver operating characteristic,End user,Computer science,Error detection and correction,Artificial intelligence,Artificial neural network,Sophistication,Machine learning
Conference
Citations 
PageRank 
References 
3
0.53
0
Authors
2
Name
Order
Citations
PageRank
Russell C. Eberhart1184.73
Roy W. Dobbins2163.94