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Radiomics in the diagnosis of glioblastoma
artificial intelligence
machine learning
glioblastoma
radiomics
Bibliogr. s. e465-e466
Radiomics is a process of extracting many quantitative data obtained from medical images and analysing them. In neuroradiology it may be used to discover magnetic resonance imaging (MRI) features of glioblastomas that are impossible to identify by human vision alone. In this article, the authors describe the methodology and their first experience in creating a predictive model based on radiomic features obtained from the preoperative MRI examination of patients with glioblastoma. Early identification of malignant glioblastoma subtypes characterized by different prognoses and responses to treatment would greatly facilitate the implementation of targeted therapy, which appears to be the future of glioblastoma treatment.
| dc.abstract.en | Radiomics is a process of extracting many quantitative data obtained from medical images and analysing them. In neuroradiology it may be used to discover magnetic resonance imaging (MRI) features of glioblastomas that are impossible to identify by human vision alone. In this article, the authors describe the methodology and their first experience in creating a predictive model based on radiomic features obtained from the preoperative MRI examination of patients with glioblastoma. Early identification of malignant glioblastoma subtypes characterized by different prognoses and responses to treatment would greatly facilitate the implementation of targeted therapy, which appears to be the future of glioblastoma treatment. | |
| dc.contributor.author | Kwiatkowska-Miernik, Agnieszka | |
| dc.contributor.author | Mruk, Bartosz | |
| dc.contributor.author | Sklinda, Katarzyna | |
| dc.contributor.author | Zaczyński, Artur | |
| dc.contributor.author | Walecki, Jerzy | |
| dc.date.accessioned | 2024-07-24T07:04:33Z | |
| dc.date.available | 2024-07-24T07:04:33Z | |
| dc.date.issued | 2023 | |
| dc.date.openaccess | 0 | |
| dc.description.accesstime | w momencie opublikowania | |
| dc.description.additional | Bibliogr. s. e465-e466 | |
| dc.description.physical | e461-e466 | |
| dc.description.version | ostateczna wersja wydawcy | |
| dc.description.volume | 88 | |
| dc.identifier.doi | 10.5114/pjr.2023.132168 | |
| dc.identifier.issn | 1899-0967 | |
| dc.identifier.uri | https://ruj.uj.edu.pl/handle/item/389312 | |
| dc.language | eng | |
| dc.language.container | eng | |
| dc.rights | Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0 Międzynarodowa | |
| dc.rights.licence | CC-BY-NC-ND | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.pl | |
| dc.share.type | otwarte czasopismo | |
| dc.subject.en | artificial intelligence | |
| dc.subject.en | machine learning | |
| dc.subject.en | glioblastoma | |
| dc.subject.en | radiomics | |
| dc.subtype | ReviewArticle | |
| dc.title | Radiomics in the diagnosis of glioblastoma | |
| dc.title.journal | Polish Journal of Radiology | |
| dc.type | JournalArticle | |
| dspace.entity.type | Publication | en |
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