Information extraction technology can extract the key information in free-text electronic medical records, helping the information management and subsequent information analysis of the hospital. Therefore, the main process of free-text electronic medical record information extraction was simply introduced, the research results of single extraction and joint extraction methods for three most important types of information:named entity, entity assertion and entity relation in the past few years were studied, and the methods, datasets, and final effects of these results were compared and summarized. In addition, an analysis of the features, advantages and disadvantages of several popular new methods, a summarization of commonly used datasets in the field of information extraction of free-text electronic medical records, and an analysis of the current status and research directions of related fields in China was carried out.

Aiming at poor control effect of Fractional Order Proportional-Integral-Derivative (FOPID) controller and the characteristics of wide range and high complexity of parameter tuning for FOPID controller, an improved Particle Swarm Optimization (PSO) method was proposed to optimize the parameters of FOPID controller. In the proposed algorithm, the upper and lower limits of inertial weight coefficients in PSO were defined and decreased nonlinearly with the iteration times in form of Gamma function, meanwhile, the inertia weight coefficients and learning factors of particles were dynamically adjusted according to the fitness value of particles, making the particles keep reasonable motion inertia and learning ability, and improving self-adaptive ability of the particles. Simulation experiments show that the improved PSO algorithm has faster convergence rate and higher convergence accuracy than the standard PSO algorithm in optimizing the parameters of FOPID controller, which makes the FOPID controller obtain better comprehensive performance.