Post-transplant recipients can develop a large number of complications post-surgery due to the magnitude of the treatment and the need for heavy medications in the form of immunosuppressants. Thus, preoperative patient optimization and patient selection remains of paramount importance in getting the best possible outcomes post-transplant. We would try and utilize artificial intelligence classifiers in the form of artificial neural networks, decision tree classifiers, random forest and naïve bayes classification models to try and develop better predictive tools and scoring systems with our main focus on transplant outcomes.
Collaboration
