We have created a machine learning model to evaluate the risk of relapse in lung cancer patients.

This model uses mutational data from lung cancer patients, as described in Evaluate the probability of relapse in patients with lung cancer. The expression values are the log2 values of the expression plus 1.

Patient’s data:

Pathological nodes:
Pathological tumour:
RAD51 expression:
ADGRF5 expression:
COCH expression:
SLC2A1 expression:
CLU expression:
ZDHHC7 expression:
LRFN4 expression:
AP2A2 expression:

Expression values are Affymetrix HG-U133A arrays normalized with RMA (Robust Multiarray Averaging) method.

Please note that it is impossible to predict the future with certainty, and a physician must always interpret these predictions to make a diagnosis.

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