Name
Title | ||
|---|---|---|
Handling limited datasets with neural networks in medical applications: A small-data approach. |
Abstract | ||
|---|---|---|
•A novel framework enables NN analysis in medical applications involving small datasets.•An accurate model for trabecular bone strength estimation in severe osteoarthritis is developed.•Model enables non-invasive patient-specific prediction of hip fracture risk.•Method of multiple runs mitigates sporadic fluctuations in NN performance due to small data.•Surrogate data test is used to account for random effects due to small test data. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.artmed.2016.12.003 | Artificial Intelligence in Medicine |
Keywords | Field | DocType |
Predictive modelling,Small data,Regression neural networks,Osteoarthritis,Compressive strength,Trabecular bone | Data mining,Data collection,Predictor variable,Small data,Regression,Computer science,Artificial intelligence,Predictive modelling,Artificial neural network,Surrogate data,Standard error,Machine learning | Journal |
Volume | ISSN | Citations |
75 | 0933-3657 | 8 |
PageRank | References | Authors |
0.65 | 8 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Torgyn Shaikhina | 1 | 16 | 1.59 |
| N. A. Khovanova | 2 | 23 | 2.72 |