Name
Title | ||
|---|---|---|
Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in AD. |
Abstract | ||
|---|---|---|
•Providing a measure of the uncertainty of predictions at patient-level is paramount to guide clinicians in risk-sensitive decisions.•We compared calibration methods (Platt Scaling and Isotonic Regression), Conformal Predictors, and Venn-ABERS predictors on assessing the uncertainty of predictions at patient-level, using different classifiers.•We propose an ensemble-based model where calibrated predictions from multiple pairs (classifier, uncertainty method) are combined to predict whether a given MCI patient will convert to AD. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.jbi.2019.103350 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Prognostic prediction,Mild cognitive impairment,Alzheimer’s disease,Uncertainty at patient-level,Venn-ABERS,Conformal prediction | Venn diagram,Data mining,Computer science,Isotonic regression,Decision support system,Ground truth,Artificial intelligence,Probabilistic logic,Platt scaling,Classifier (linguistics),Machine learning,Calibration | Journal |
Volume | ISSN | Citations |
101 | 1532-0464 | 2 |
PageRank | References | Authors |
0.36 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Telma Pereira | 1 | 7 | 2.53 |
| Sandra Cardoso | 2 | 5 | 1.40 |
| Manuela Guerreiro | 3 | 2 | 0.36 |
| Alexandre de Mendonça | 4 | 7 | 2.13 |
| Sara C. Madeira | 5 | 1242 | 66.91 |