Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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

    The objective of this work was to determine and compare the physiological changes in some: blood components (packed cell volume and hemoglobin) and plasma biochemical parameters (glucose, total protein, albumin, cholesterol and triglycerides) under 3 day of different types of stress: water deprivation, starvation, overcrowding and handling stress. Twenty five male Wister rats weighted 100-120 gm, were divided randomly into five groups: control, water deprivation, starvation, overcrowding and handling stress. On the third day of stress the animals anesthetized for blood collection; the results of blood component revealed a significant increase in PCV and a significant decrease in Hb of water deprivation group and starva

The problem of the study and its significance:

           Due to the increasing pressures of life continually, and constant quest behind materialism necessary and frustrations that confront us daily in general, the greater the emergence of a number of cases of disease organic roots psychological causing them because of severity of a lack of response to conventional treatments (drugs), and this is creating in patients a number of emotional disorders resulting from concern the risk of disease

     That is interested psychologists and doctors searchin

According to the famous saying of the medieval physician Paracelsus, "There is no substance without poison. Only the dose determines the extent of the toxic effect." Here, the effect of monosodium glutamate (MSG) on human health and the risks to the health of its frequent use in the short term was addressed and the long term was evaluated according to the studies of several researchers specializing in this regard. Monosodium glutamate (MSG) is known as one of the most popular food additives that classified as a flavor enhancer. Parts of the evidence were reviewed from the literature explaining its effect on immune system cells in addition to metabolic disorders by exposing individuals to obesity and what is known as metabolic syndrome, as w

This study aims to identify the impact of using the infrastructure of the Information Technology (IT) on the performance of human resources in the public universities. This process is done by doing research in the size, quality, and efficiency of the performance, also speed of achievement and simplification of procedures. Diyala University was chosen for the diagnosis through the opinions and attitudes of its employees.  Consequently, suggestions that contribute to improve the performance of the employees and thus its overall performance are obtained. Another objective of this study is identifying the human resources which are currently used in academic institutions and educational services systems because the significant role of th

The research aims present to highlight the importance of creating construction Organizational appropriate to achieve strategic success and reduce many of the negative effects experienced by organizations has been developing his questionnaire especially so was distributed to a sample of workers in the Asia-cellular as sample included (60) responsive 0 and can embody intellectual dilemma following questions (What are the dimensions of the organizational infrastructure, and what are the justifications for carrying out the reform and development cleared the organizational structure to make it more flexible) to contribute to the achievement of the strategic requirements for success of the organization surveyed.
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