Principles of artificial intelligence in radiooncology.
| Publicado en: | Strahlentherapie und Onkologie Vol. 201; no. 3; pp. 210 - 236 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2025
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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=183132067&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183132067 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01797158 NZE jtl: Strahlentherapie und Onkologie issn: 01797158 maglogo: N pubinfo: dt: Mar2025 vid: 201 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 183132067 178850579 10.1007/s00066-024-02272-0 183132067 ppf: 210 ppct: 26 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Principles of artificial intelligence in radiooncology. aug: au: Huang, Yixing Gomaa, Ahmed Höfler, Daniel Schubert, Philipp Gaipl, Udo Frey, Benjamin Fietkau, Rainer Bert, Christoph Putz, Florian affil: https://ror.org/00f7hpc57 Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 91054, Erlangen, Germany sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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