This chapter presents two interesting applications of PSO in bioinformatics and medical informatics. The first consists of the adaptation of probabilistic neural network models for medical classification tasks. The second application employs the unified PSO algorithm to tackle magnetoencephalography problems. Our main goal is to clarify crucial points where PSO interferes with the employed computational models and provide details on the formulation of the corresponding optimization problems and experimental settings. Indicative results are reported to illustrate the workings of the algorithms and provide representative samples of their performance.