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| 001 | 136844 | ||
| 005 | 20240229105103.0 | ||
| 024 | 7 | _ | |a 10.1016/j.radonc.2018.03.004 |2 doi |
| 024 | 7 | _ | |a pmid:29598835 |2 pmid |
| 024 | 7 | _ | |a 0167-8140 |2 ISSN |
| 024 | 7 | _ | |a 1879-0887 |2 ISSN |
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| 037 | _ | _ | |a DKFZ-2018-01282 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Zwanenburg, Alexander |0 P:(DE-He78)740e39a4deb404c1afb2623fdb730543 |b 0 |e First author |
| 245 | _ | _ | |a Why validation of prognostic models matters? |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2018 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1558086094_8585 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a G947 NCT DD Liaison HZDR |
| 520 | _ | _ | |a Prognostic models are powerful tools for treatment personalisation. However, not all proposed models work well when validated using new data, despite impressive results being reported initially. Here, we will use a hands-on approach to highlight important aspects of prognostic modelling, as well as to demonstrate methods to generate generalisable models. |
| 536 | _ | _ | |a 317 - Translational cancer research (POF3-317) |0 G:(DE-HGF)POF3-317 |c POF3-317 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
| 700 | 1 | _ | |a Löck, Steffen |0 P:(DE-HGF)0 |b 1 |e Last author |
| 773 | _ | _ | |a 10.1016/j.radonc.2018.03.004 |g Vol. 127, no. 3, p. 370 - 373 |0 PERI:(DE-600)1500707-8 |n 3 |p 370 - 373 |t Radiotherapy and oncology |v 127 |y 2018 |x 0167-8140 |
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