introduction: health care classifications are essential tools for collecting and processing health-related information. they also provide a unified language for interdisciplinary communications. nursing data is important for extension of knowledge, evaluating the quality and effectiveness of nursing care, and supporting human resource planning. therefore, an integrated system for collecting, st...

the dna microarray is an important technique that allows researchers to analyze many gene expression data in parallel. although the data can be more significant if they come out of separate experiments, one of the most challenging phases in the microarray context is the integration of separate expression level datasets that have gathered through different techniques. in this paper, we present a...

Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...

introduction: world health organization (who) attempts to update icd-10 (international classification diseases-10 th version) according to the required information of the scientific community. in this study, changes of icd-10 will be reviewed in updating process. methods: the data of the present descriptive study was extracted from the world health organization website. the data were interprete...

designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing fuzzy learning classifier (flc) systems. conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. in thispaper new entities namely precision and recall from the field of information retrieval (ir)systems is adapted as alternative...

this paper introduces a novel methodology for the segmentation of brain ms lesions in mri volumes using a new clustering algorithm named scpfcm.  scpfcm uses membership, typicality and spatial information to cluster each voxel. the proposed method relies on an initial segmentation of ms lesions in t1-w and t2-w images by applying scpfcm algorithm, and the t1 image is then used as a mask and is ...