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Survival analysis for lung cancer patients: A comparison of Cox regression and machine learning models.

Sebastian GermerChristiane RudolphLouisa LabohmAlexander KatalinicNatalie RathKatharina RauschBernd Holleczeknull nullHeinz Handels
Published in: International journal of medical informatics (2024)
The studied methods are highly relevant for epidemiological researchers to create more accurate survival models, which can help physicians make informed decisions about appropriate therapies and management of patients with lung cancer, ultimately improving survival and quality of life.
Keyphrases
  • machine learning
  • end stage renal disease
  • free survival
  • primary care
  • chronic kidney disease
  • ejection fraction
  • newly diagnosed
  • peritoneal dialysis
  • high resolution
  • big data