Variable selection in Logistic regression model with genetic algorithm.

Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process.

[Research progress and prospect of electrical properties tomography for prostate].

We reviewed the research progress and prospect of electrical properties tomography for prostate in this paper. After the introduction of the basic principles of electrical impedance tomography (EIT) and magnetic resonance electric impedance tomography (MREIT), we presented the applications of the two techniques in electrical properties tomography of the prostate in detail. We then discussed the application prospects of induced current magnetic resonance electric impedance tomography (IC-MREIT) and magnetic resonance electrical properties tomography (MREPT) in the diagnoses of prostate cancer.