This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

In the United States, the pharmaceutical industry is actively devising strategies to improve the diversity of clinical trial participants. These efforts stem from a plethora of evidence indicating that various ethnic groups respond differently to a given treatment. Thus, increasing the diversity of trial participants would not only provide more robust and representative trial data but also lead to safer and more effective therapies. Further diversifying trial participants appear straightforward, but it is a complex process requiring feedback from multiple stakeholders such as pharmaceutical sponsors, regulators, community leaders, and research sites. Therefore, the objective of this paper is to describe three viable strategies that can p

    In this article, we introduce and study two new families of analytic functions by using strong differential subordinations and superordinations associated with Wanas differential operator/. We also give and establish some important properties of these families.

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

Form the series of generalization of the topic of supra topology is the generalization of separation axioms . In this paper we have been introduced (S * - SS *) regular spaces . Most of the properties of both spaces have been investigated and reinforced with examples . In the last part we presented the notations of supra *- -space ( =0,1) and we studied their relationship with (S * - SS *) regular spaces.

Let R be a ring with identity and M be a right unitary R-module. In this paper we
introduce the notion of strongly coretractable modules. Some basic properties of this
class of modules are investigated and some relationships between these modules and
other related concepts are introduced. 

     This article contains a new generalizations of Ϻ-hyponormal operators which is namely (Ϻ,θ)-hyponormal operator define on Hilbert space H.  Furthermore, we investigate some properties of this concept such as the product and sum of two (Ϻ, θ)-hyponormal operators, At the end the operator equation  where  ,  has been used for getting several characterization of (Ϻ,θ)-hyponormal operators.  

    In this study, the concept of fuzzy α-topological vector space is introduced by using the concept  fuzzy α-open set , some properties of fuzzy α-topological vector spaces are proved .We also show that the space is -space iff every singleton set is fuzzy α- closed .Finally, the convex property and its relation with the interior points are discussed.

The growth curves of the children are the most commonly used tools to assess the general welfare of society. Particularity child being one of the pillars to develop society; through these tools, we can path a child's growth physiology. The Centile line is of the important tools to build these curves, which give an accurate interpretation of the information society, also respond with illustration variable age. To build standard growth curves for BMI, we use BMI as an index. LMSP method used for finding the Centile line which depends on four curves represents Median, Coefficient of Variation, Skews, and Kurtosis. These can be obtained by modeling four parameters as nonparametric Smoothing functions for the illustration variable. Ma