In this study, biomechanical behaviors of three different screw materials (stainless steel, titanium and cobalt-chromium) have analyzed to fix with triangle fixation under axial loading in femoral neck fracture and which material is best has been investigated. Point cloud obtained after scanning the human femoral model with the three dimensional (3D) scanner and this point cloud has been converted to 3D femoral model by Geomagic Studio software. Femoral neck fracture was modeled by SolidWorks software for only triangle configuration and computer-aided numerical analyses of three different materials have been carried out by AnsysWorkbench finite element analysis (FEA) software. The loading, boundary conditions and material properties have prepared for FEA and Von-Misses stress values on upper and lower proximity of the femur and screws have been calculated. At the end of numerical analyses, the best advantageous screw material has calculated as titanium because it creates minimum stress at the upper and lower proximity of the fracture line.
Low back pain (LBP) is one of the common problems encountered in medical applications. This paper proposes two expert systems (artificial neural network and adaptive neuro-fuzzy inference system) for the assessment of the LBP level objectively. The skin resistance and visual analog scale (VAS) values have been accepted as the input variables for the developed systems. The results showed that the expert systems behave very similar to real data and that use of the expert systems can be used to successfully diagnose the back pain intensity. The suggested systems were found to be advantageous approaches in addition to existing unbiased approaches. So far as the authors are aware, this is the first attempt of using the two expert systems achieving very good performance in a real application. In light of some of the limitations of this study, we also identify and discuss several areas that need continued investigation.
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