Scientific users consider cloud platform as a popular distributed computing platform for deploying large scale medical workflow applications. These applications can be executed cost-effectively in IaaS cloud service model, as it provides scientific users with infinite pool of heterogeneous resources and pay-peruse billing model. In the proposed work, the medical science applications are mapped to the IaaS resources based on the billing scheme and the billing granularity of the cloud resources. The goal of the proposed work is to schedule medical workflow applications using discrete particle swarm optimization (DPSO) for minimizing makespan and cost. The schedule generated by the DPSO is rescheduled based on the task runtime and resource billing granularity. The proposed approach is evaluated on Epigenomic medical workflow application.