Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained were 96.5% and 93.47%, respectively, before applying balancing to the data. In addition, 98.59% and 97.18%, respectively, after applying the balancing technique The extreme gradient boosting (XGBoost) technique had been applied to selecting the important features and the Pearson correlation for finding the correlation between features.
Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
Porous silicon was prepared by using electrochemical etching process. The structure, electrical, and photoelectrical properties had been performed. Scanning Electron Microscope (SEM) observations of porous silicon layers were obtained before and after rapid thermal oxidation process. The rapid thermal oxidation process did not modify the morphology of porous layers. The unique observation was the pore size decreased after oxidation; pore number and shape were conserved. The wall size which separated between pore was increased after oxidation and that effected on charge transport mechanism of PS
Isocratic high performance liquid chromatography on reversed phase a (150x 4.6 mm I.D), 5 ?m ?-Bondapak RP-8 column (with acidic mobile phase allow the separation of doxcycycline hydrochloride with low detection limit of 0.2 µg/ml detected by UV set at 226 nm. The method was validated for Doxycycline between 0.156- to 5 µg/ml. The concentration of doxycycline was assessed in two single dose randomized crossover studies with intervals of one week between two period. In sera of 20 adults healthy male volunteers with average age of (42 + 10) year, body weight 48-85 kg, body height of (160-185cm) after a single dose of doxycycline hydrochoride 100 mg in form of capsules were orally administrated for both formulations. The blood sa
... Show MoreThe effects of shot peening treatment (SPT) were studied at (10,20, and 30) minutes on the rotating bending fatigue behavior and the behavior of the alloy steel DIN 41Cr4 vibrations. The hardness test, tensile test, constant amplitude fatigue tests, and the vibration measurements were performed on samples with and without cracks at room temperature (RT), also, the fracture surface was examined and analyzed by a Scanning Electron Microscope (SEM). The results of the investigations, for example, Stress to Number of cycles to failure (S-N) curves, fatigue strength improvement factor of 5% to 10%, the decreasing percentage of maximum Fast Fourier Transform (FFT) acceleration of the shot-peened condition were compared to untr
... Show More<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121
... Show MoreBACKGROUND: Burkholderia cepacia adhesion and biofilm formation onto abiotic surfaces is an important feature of clinically relevant isolates. The in vitro biofilm formation of B. cepacia onto coated indwelling urinary catheters (IDCs) with moxifloxacin has not been previously investigated. OBJECTIVES: To examine the ability of B. cepacia to form biofilms on IDCs and the effect of coating IDCs with moxifloxacin on biofilm formation by B. cepacia in vitro. MATERIAL AND METHODS: The adhesion of B. cepacia to coated and uncoated IDCs with moxifloxacin was evaluated. Pieces of IDCs were coated with moxifloxacin (adsorption method). The spectrophotometric method was used to check moxifloxacin leaching into tubes. Coated and uncoated tubes were i
... Show More