A Bayesian model for fusing biomedical labels
Tingting Zhu, Gari D. Clifford, David Andrew Clifton · Institution of Engineering and Technology eBooks · 2016
Chapter Contents: 7.1 Background 7.2 A generative model of annotators 7.2.1 The ground truth model 7.2.2 The annotator model 7.3 Bayesian probability in parameter estimation 7.4 The Bayesian continuous-valued label aggregator 7.4.1 The MAP approach of the BCLA model 7.4.2 Convergence criteria for the BCLA-MAP model 7.4.3 Learning from incomplete data using the BCLA-MAP model 7.5 Data description 7.5.1 Simulated QT dataset with independent annotators 7.5.2 The 2006 PhysioNet challenge QT dataset 7.5.3 Methodology of validation and comparison 7.6 Results and discussion 7.6.1 Simulated dataset 7.6.2 PCinC QT dataset 7.7 Conclusion and future work Acknowledgement References