Risk modelling of time to lung cancer diagnosis
- To determine the best predictors of developing lung cancer after a screening round based on participant characteristics and CT scan morphology.
- To observe the effect of different screening intervals.
- To ultimately predict the time frame a screening participant is likely to develop cancer in, should they develop it at all.
Bram van Ginneken, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Colin Jacobs, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Cornelia Schaefer-Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Mathias Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Max Argus, MSc. Radboud University Medical Center, the Netherlands
Anton Schreuder, MD. Radboud University Medical Center, the Netherlands
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Lung cancer risk to personalise annual and biennial follow-up computed tomography screening.
Schreuder A, Schaefer-Prokop CM, Scholten ET, Jacobs C, Prokop M, van Ginneken B
Thorax. 2018 Mar PUBMED