Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review.
Radiomics is a quantitative tool for digital image analysis. This systematic review aims to investigate the scientific articles to evaluate the potential implications of Radiomics analysis in Dentomaxillofacial Radiology (DMFR). Studies regarding Radiomics applications in DMFR and human samples, in...
| Publicado en: | Journal of Imaging Informatics in Medicine Vol. 38; no. 4; pp. 2428 - 2462 |
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| Autores principales: | , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187278950&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187278950 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 29482925 NR3A jtl: Journal of Imaging Informatics in Medicine issn: 29482925 maglogo: N pubinfo: dt: Aug2025 vid: 38 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 187278950 187278950 187278950 10.1007/s10278-024-01307-3 187278950 ppf: 2428 ppct: 34 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review. aug: au: Tarakçı, Özge Dönmez Kış, Hatice Cansu Amasya, Hakan Öztürk, İrem Karahan, Emre Orhan, Kaan affil: https://ror.org/04a7vn235 Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Izmir Tınaztepe University, Izmir, Turkey sug: subj: Radiomics Evaluation Radiography, Dental Radiomics Adverse Effects Serial Publications Face Radiography Maxilla Radiography Human Male Female Systematic Review PubMed Embase Medline Cochrane Library Descriptive Statistics Checklists Support Vector Machine Decision Trees Diagnosis, Computer Assisted Imaging, Three-Dimensional Image Interpretation, Computer Assisted Male Female ab: Radiomics is a quantitative tool for digital image analysis. This systematic review aims to investigate the scientific articles to evaluate the potential implications of Radiomics analysis in Dentomaxillofacial Radiology (DMFR). Studies regarding Radiomics applications in DMFR and human samples, in vivo study, a case reports/series if ≧5 samples were included, while case reports/series if < 5 samples, articles other than in English, abstracts without full text, and studies published before 2015 were excluded. Fifty-one articles were selected from 3789 literatures. The QUADAS-2 tool was used for risk of bias assessment. The accuracy of predicting dentomaxillofacial pathologies was considered as the primary outcome, and the modeling type of Radiomics was considered as the secondary outcome. A meta-analysis could not be performed due to the lack of information and standardization among the reported accuracies. The reported accuracies were found between 0.66 and 99.65%. Logistic regression (n = 6) was found to be the most common Radiomics modeling type, followed by Support Vector Machine and Decision Tree (n = 5). Second-order statistics (n = 38) was the most common type of Radiomics application, followed by first-order (n = 26), higher-order (n = 20), and shape-based (n = 15) statistics. Further work is needed to increase standardization in the Radiomics workflow. Quantitative image analysis is an alternative tool for conventional visual radiographic evaluation. Radiomics systems depend on elements such as imaging modality, feature type, data mining, or statistical method. Radiomics applications do not justify digital transformation on their own, but the potential of its integration into the digital workflow is considerable. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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