Backgrond: One of the major causes of impaired movements post-stroke is the abnormal phasing of paralytic muscles. Many studies suggested that inappropriate muscle phasing may be associated with enhanced transmission in the monosynaptic Group Ia afferent pathway in the affected limb of post-stroke patients and Group Ia reflexes are abnormally elevated and fail to decrease in amplitude during locomotion.
Objectives: This study was conducted to identify the changes in the Soleus muscle H-reflex excitability at rest in the affected lower limb of post-stroke patients as compared to the contra lateral side and of normal controls.
Patients and methods: The excitability of the m
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreThis paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them in terms of accuracy.
This study aims to determine the exposure of dentists to radiation resulting from the use of light therapy units and to assess their risk and impact on dental clinics. This study was conducted in private dental clinics in the city of Erbil in northern Iraq. Surveys were conducted to collect information about light-curing units. The results were analysed using the multi-response logistic regression to determine the factors affecting the radiation values of light-curing units. The results of the study showed that five major variables have a major effect by radiation. This is shown with a value of P ≤ 0.05. Typical treatment times with radiant light, with a typical number of daily restorations, may exceed the risk limits for
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