“Development of a probabilistic network for clinical pathways based on patient cohort characteristics, outcome-indicators and clinical workflow analysis to create artificial patients with prostatic adenocarcinoma”
The main focus of the work is the generation of a probabilistic network in order to subsequently generate artificial prostate cancer patient data. This network, which is based on current study data, should enable a classification of realistic patients. The classification is based on their characteristics, guideline adherence or deviation of the treatment as well as the resulting outcome indicators.
- main aim: generation of a probabilitic network for the creation of artifical prostate cancer patient data
- classification of realistic patients
- classification based on characteristics, guidelin adherence, deviation of the treatment, resulting, outcome indicators
Andrea Riedel (master's degree candidate)