Machine learning for optimized individual survival predictio…

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45
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2022
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Work Details
  • DOI 10.1007/s00432-022-04063-5
  • PMID https://pubmed.ncbi.nlm.nih.gov/35616729
  • OpenAlex ID W4281561971
  • Type Article
  • Language EN
  • Published 26 May 2022
  • Volume 149 (5)
  • Pages 1691–1702
  • Source Journal of Cancer Research and Clinical …
  • Publisher Springer Science+Business Media
  • FWCI 5.34
  • Countries 1
  • Institutions 4
  • Added 10 Oct 2025
  • Updated 16 Oct 2026
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Machine learning for optimized individual survival prediction in resectable upper gastrointestinal cancer

Article 2022 EN Hybrid

PURPOSE: Surgical oncologists are frequently confronted with the question of expected long-term prognosis. The aim of this study was to apply machine learning algorithms to optimize survival prediction after oncological resection of gastroesophageal cancers. METHODS: Eligible patients underwent oncological resection of gastric or distal esophageal cancer between 2001 and 2020 at Heidelberg Univers…

45

Citations

25

References

11

Authors

5.34

FWCI

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UN Sustainable Development Goals
1 SDGs
Authors & Affiliations
11 authors
#AuthorInstitutionsORCID
1 Jin‐On Jung University of Cologne (DE) Heidelberg University (DE) +2
2 Nerma Crnovrsanin Heidelberg University (DE) University Hospital Heidelberg (DE)
3 Naita Maren Wirsik University of Cologne (DE) Heidelberg University (DE) +2 —
4 Henrik Nienhüser Heidelberg University (DE) University Hospital Heidelberg (DE)
5 Leila Peters Heidelberg University (DE) University Hospital Heidelberg (DE) —
6 Felix Popp University of Cologne (DE) University Hospital Cologne (DE)
7 A. Schulze Heidelberg University (DE) University Hospital Heidelberg (DE)
8 Martin Wagner Heidelberg University (DE) University Hospital Heidelberg (DE)
9 Beat Peter Müller-Stich Heidelberg University (DE) University Hospital Heidelberg (DE)
10 Markus Wolfgang Büchler Heidelberg University (DE) University Hospital Heidelberg (DE)
11 Thomas Schmidt Corresponding Heidelberg University (DE) University Hospital Heidelberg (DE) +1
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