Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

KE Sharquie, AA Noaimi, AG Al-Ghazzi, Journal of Dermatology & Dermatologic Surgery, 2015 - Cited by 19

In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.

        Financial inclusion refers to the access of financial services at low cost and high-quality from the formal financial sector to all segments of society, especially marginalized groups, and then use and benefit from them. Financial inclusion is also associated with banking stability, as well as with financial integrity and financial protection for the consumer, therefore, it achieves a number of objectives, the most important of which is to support and enhance banking stability. This is what made it attract the attention of many countries and central banks recently.

     The study aims to show the impact of financial inclusion indicators on ban

Five novel nickel, iron, cobalt, copper, and mercury complexes were synthesized from tetraazamacrocyclic Schiff base ligand (L), which were derived from 3-(4-(dimethyl amino) benzylidene) pentane-2,4-dione and 1,2- diaminocyclohexane in a 2:2 molar ratio. Many physico-chemical and spectroscopic techniques, including melting point, 1HNMR, 13CNMR, elemental analysis, molar conductance, magnetic susceptibility, UV-Vis, FT-IR, and thermogravimetric analysis (TGA), were used to characterize the Schiff base ligand and all metal complexes. The octahedral geometry of all the complexes [MLCl2] is confirmed by spectroscopic analyses. All substances' biological properties, such as their in vitro antioxidant activity or level of free radical scavenging