| dc.contributor.author | Jenul, Anna | |
| dc.contributor.author | Stokmo, Henning Langen | |
| dc.contributor.author | Schrunner, Stefan | |
| dc.contributor.author | Hjortland, Geir Olav | |
| dc.contributor.author | Rootwelt-Revheim, Mona-Elisabeth | |
| dc.contributor.author | Tomic, Oliver | |
| dc.date.accessioned | 2024-02-12T10:39:19Z | |
| dc.date.available | 2024-02-12T10:39:19Z | |
| dc.date.created | 2024-01-18T12:09:42Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Computer Methods and Programs in Biomedicine. 2023, 244 . | |
| dc.identifier.issn | 0169-2607 | |
| dc.identifier.uri | https://hdl.handle.net/11250/3116845 | |
| dc.description.abstract | • We model and predict the overall survival in patients with high-grade gastroenteropancreatic neuroendocrine neoplasms. • Novel ensemble feature selectors RENT and UBayFS are assessed for predictive performance, stability, and interpretability. • Data- as well as expert-driven feature selection (with and without prior knowledge) are evaluated. • Our results show that both methods allow accurate predictions and have a stabilizing effect on the model parameters. • RENT and UBayFS identify influencing factors for overall survival and support clinical experts in decision-making. | |
| dc.description.abstract | Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival | |
| dc.language.iso | eng | |
| dc.relation.uri | https://www.sciencedirect.com/science/article/pii/S0169260723006004 | |
| dc.subject | Nukleærmedisin | |
| dc.subject | Nuclear medicine | |
| dc.subject | Maskinlæring | |
| dc.subject | Machine learning | |
| dc.title | Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival | |
| dc.title.alternative | Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival | |
| dc.type | Peer reviewed | |
| dc.type | Journal article | |
| dc.description.version | publishedVersion | |
| dc.subject.nsi | VDP::Radiologi og bildediagnostikk: 763 | |
| dc.subject.nsi | VDP::Radiology and diagnostic imaging: 763 | |
| dc.source.pagenumber | 14 | |
| dc.source.volume | 244 | |
| dc.source.journal | Computer Methods and Programs in Biomedicine | |
| dc.identifier.doi | 10.1016/j.cmpb.2023.107934 | |
| dc.identifier.cristin | 2229464 | |
| dc.relation.project | Helse Sør-Øst RHF: 2018022 | |
| cristin.ispublished | true | |
| cristin.fulltext | original | |
| cristin.qualitycode | 1 | |
