Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum error rate, and the test maximum accuracy for K_value selection with an accuracy of 86.24%. Where the distance metric has been assigned using the Euclidean approach. From previous models, it seems that Breast Cancer Grade2 is the most prevalent type. For the future perspective, a comparative study could be performed to compare the supervised and unsupervised data mining algorithms.
Background: Ejection fraction have been used frequently
for assessment of the left ventricular function, but can be
associated with errors in which myocardial performance
index have been used as another parameter to measure the
left ventricular function.
Objective: selecting another echocardiography parameter
for the assessment of myocardial in function instead of the
ejection fraction.
Methods: 160 patients referred to the echocardiogram unit
from the period december 2007 to august 2008 requesting
assessment of left ventricular function. After clinical
examination, routine blood tests; chest x-ray and
electrocardiographic recording have been completed. All
patients informed to come for this unit af
Background: Various abnormalities in myocardial repolarization assessed by QT variability index (QTVI) in diabetics are associated with high risk to ventricular arrhythmia. The increase in cardiovascular morbidity and mortality appears to relate to the synergism of hyperglycemia with dyslipidemia, hypertension and obesity in addition to disturbed myocardial repolarization.
Objectives: The aim of the present study was to estimate and evaluate an index of myocardial repolarization instability (QTVI) in patients with DM on insulin or oral hypoglycemic drugs in comparison with healthy individuals.
Patients and Methods: The study was conducted on fifty six (56), middle-aged patients with DM of either sex in addition to age-matched healt
Background: Atherosclerosis is a diffuse disease process, being present in one vascular bed predicts its presence in the others. Ankle –brachial pressure index (ABI) is a non invasive test proved to be sensitive and specific in detecting and assessing the severity of peripheral arterial disease.
Patients and Methods: One hundred fifty patients (150) were enrolled in this study, from January - June 2007; all were referred to the Iraqi Centre for Heart Diseases (I.C.H.D.) for further evaluation, with request for further assessment of CAD or lower extremity peripheral arterial disease. Clinical data and physical examination were performed; ABI was calculated by measurement of systolic pressure on both ankl
Fac Med Baghdad 2014; Vol.56, No.2 Received: April. 2014 Accepted May. 2014
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Let be a connected graph with vertices set and edges set . The ordinary distance between any two vertices of is a mapping from into a nonnegative integer number such that is the length of a shortest path. The maximum distance between two subsets and of is the maximum distance between any two vertices and such that belong to and belong to . In this paper, we take a special case of maximum distance when consists of one vertex and consists of vertices, . This distance is defined by: where is the order of a graph .
In this paper, we defined – polynomials based on
... Show MoreThe present study deals with the assessment of water Quality Index to theAl-
Khadhimiya Groundwater city, by collection groundwater from 13wells during four
seasons, subjecting the samples to a comprehensive physicochemical analysis. The
13 parameters have been considered: pH, total hardness, calcium, magnesium,
turbidity, nitrate, electrical conductivity, total dissolved solid, Sulfate, Chloride,
zinc, manganic, and iron, that are used for calculating the WQI. From the result
shown, the most groundwater quality lies in Unfit for human drinking purpose. The
wells (1 and 11) and wells (3 and 10) were a bad water quality for drinking purpose
since they lie in poor and in very poor respectively according to the WQI.
A huge potential from researchers was presented for enhancing the nonlinear optical response for materials that interacts by light. In this work, we study the nonlinear optical response for chemically prepared nano- fluid of silver nanoparticles in de-ionized water with TSC (Tri-sodium citrate) protecting agent. By the means of self-defocusing technique and under CW 473 nm blue laser, the reflected diffraction pattern were observed and recorded by CCD camera. The results demonstrate that, the Ag nano-fluid shows a good third order nonlinear response and the magnitude of the nonlinear refractive index was in the order of 10−7 cm2/W. We determine the maximum change of the nonlinear refractive index and the related phase shift for the mat
... Show MoreBackground: Nodal osteoarthritis is one of the most common arthropathy worldwide, the etiology is uncertain but many biochemical markers are recognized. Many studies have shown that leptin might have a role in the pathogenesis of osteoarthritis, but little is known about the relation between serum leptin and nodal osteoarthritis.
Subjects and method: 52 women with nodal osteoarthritis and 40 apparently healthy women as a control were included in the study; serum leptin was measured in all subjects. Student t-test was applied to find out the significance of difference in the mean v
Results: There was a significant difference in the mean of serum leptin between patients and control groups.
Conclusion:
Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.