BAYESIAN MODELING OF PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS KIDNEY GRAFT SURVIVAL

摘要

An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.

主权项

1. A method for determining a patient-specific probability of renal transplant survival, said method including:
a) collecting clinical parameters from a plurality of patients and donor to create a training database, the clinical parameters; b) creating a fully unsupervised Bayesian Belief Network model using data from the training database; c) validating the fully unsupervised Bayesian Belief Network model; d) collecting the clinical parameters for an individual patient and an donor; e) receiving the clinical parameters for the individual patient and an donor into the fully unsupervised Bayesian Belief Network model; f) outputting the patient-specific probability of transplant survival from the fully unsupervised Bayesian Belief Network model to a graphical user interface for use by a clinician; and g) updating the fully unsupervised Bayesian Belief Network model using the clinical parameters for the individual patient and for the donor, and the patient-specific probability of transplant survival.