The learning unit includes the generation of a decision tree based on a breast cancer data set from radiology department using the RapidMiner software package and an elaboration of the concepts of sensitivity and specificity. Furthermore, we will apply Bayesian reasoning and give an opportunity to discuss the base rate fallacy problem and the use of electronic calculators to judge the risk. The learning unit is finished with a discussion of the barriers/facilitators of using computers/AI in hospitals to support clinical reasoning.