A robust framework epileptic seizures classification based on lightweight structure deep convolutional neural network and wavelet decomposition

Nowadays scientific evidence suggests that epileptic seizures can appear in the brain signals minutes and even hours prior to their occurrence. Advances in predicting epileptic seizures can promise a robust model in which seizures and irreparable injuries at the time of occurrence can be possible. Most of the previous automated solutions are associated with challenges such as the lack of a proper signal descriptor, the existence of a large number of features and, consequently, the time-consuming analysis, which are not considering the uncertainty issue. In this paper, efficient and fastidious classification is performed by analysing the frequency bands of the input EEG signal via discrete wavelet transform, which is relying on the deep convolutional neural network based classification. Using the EEG signals obtained from the CHEG-MIT Scalp EEG database, the implementation in the desired model is performed and the results show that the proposed model has the best response in detecting the disease from the sample signal and with the highest level of certainty to follow. To solve the uncertainty problem, the repeatability algorithm test is arranged and after K-fold cross-validation, the experimental precision of all the three evaluation factors were equal to 99.34%, 99.53%, and 99.76%, respectively

Cost-effectiveness analysis of topiramate versus phenobarbital in the treatment of children with febrile seizure in Shiraz

Background: Febrile seizure is the most common disorder in childhood, with a prevalence of 2% to 5%. There are many drugs for treatment of this disease; however, the most common prescribed medication in Iran is phenobarbital that is cheap, but it has many side effects. Topiramate is a medication with fewer side effects that is currently prescribed in Iran only for patients with epilepsy; also, it has recently been prescribed and tested for children with febrile seizure. The aim of this study was to compare the cost-effectiveness of topiramate versus phenobarbital in patients with febrile seizure in the south of Iran in 2017.Methods: This econometric cost-effectiveness and cost-utility study was conducted on 91 patients with febrile seizure to assess two strategies of oral drug therapy including phenobarbital and topiramate in 2016-2017. Of all, 51 patients were treated with phenobarbital and 40 patients received topiramate. In order to collect the required data, we followed up the patients for six months, using a randomized and single-blinded approach. In this study, a decision tree model was used. The outcomes of the model included febrile seizure and utility. The study was conducted from the perspective of the community; therefore, direct and indirect costs were included in the study. Excel and TreeAge software (2011) were used to analyze the results.Results: The results showed that topiramate was cheaper and more effective than phenobarbital. In patients in the phenobarbital and topiramate groups, the mean costs were $740 and$674 per ppp, utility scores were 0.72 and 0.82, and febrile seizure without side effects were 0.3 and 0.6, respectively. Moreover, one-way sensitivity analysis confirmed the robustness of the results of the study.Conclusion: According to the results, topiramate in patients with febrile seizure is a fully cost-effective and cost-efficient strategy that can be suggested as a better alternative for children with febrile seizure

The protective effect of hydroalcoholic extract of Ephedra pachyclada leaves on ovarian damage induced by cyclophosphamide in rat: An experimental study

Background: Cyclophosphamide (CP) is an anticancer drug that acts as an alkylation agent after metabolism in the liver. CP has toxic effects on the body’s cells, especially the reproductive system’s function, and causes infertility. Moreover, medicinal plants have few side effects and are psychologically acceptable to patients. Objective: This study aimed to investigate the impact of Ephedra pachyclada hydroalcoholic extract (EPHE) on ovarian tissue and hypothalamic-pituitary-gonadal axis in rats treated with CP. Materials and Methods: In this experimental study, 48 adult female Wistar rats (180-200 gr, 9-10 wk) were randomly assigned to 6 experimental groups (n = 8/each): (a) control; (b) sham; (c) CP; (d) CP+250 mg/kg EPHE; (e) CP+500 mg/kg EPHE; (f) CP+1000 mg/kg EPHE. On the 29th day of the experiment, serum was collected; serum concentration of the luteinizing hormone, follicle-stimulating hormone, estrogen, progesterone, and antioxidant activity were measured. The number of ovarian follicles were also counted. Results: In the CP groups, serum concentrations of follicle-stimulating hormone and luteinizing hormone significantly increased, and estrogen and progesterone significantly decreased (p ≤ 0.05). EPHE significantly compensated for the complications caused by CP and 1000 mg/kg had the greatest effect. Antioxidant reduction by CP was significantly enhanced by EPHE, especially at higher doses (p ≤ 0.05). The number of primordial, primary, secondary, and Graafian follicles showed a significant decrease in CP groups and EPHE groups showed a significant increase compared to the CP. EPHE showed that the concentration of 1000 mg/kg was more effective than other doses (p ≤ 0.05). Conclusion: In addition to proving the effect of EPHE on the hypothalamic-pituitary-gonadal axis, our investigation showed antioxidant properties, which can be an effective factor in CP-treated rats. Key words: Ephedra, Cyclophosphamide, Ovary, Follicles, Hydroalcoholic extract

A medium‐weight deep convolutional neural network‐based approach for onset epileptic seizures classification in EEG signals

Abstract Introduction Epileptic condition can be detected in EEG data seconds before it occurs, according to evidence. To overcome the related long‐term mortality and morbidity from epileptic seizures, it is critical to make an initial diagnosis, uncover underlying causes, and avoid applicable risk factors. Progress in diagnosing onset epileptic seizures can ensure that seizures and destroyed damages are detectable at the time of manifestation. Previous seizure detection models had problems with the presence of multiple features, the lack of an appropriate signal descriptor, and the time‐consuming analysis, all of which led to uncertainty and different interpretations. Deep learning has recently made tremendous progress in categorizing and detecting epilepsy. Method This work proposes an effective classification strategy in response to these issues. The discrete wavelet transform (DWT) is used to breakdown the EEG signal, and a deep convolutional neural network (DCNN) is used to diagnose epileptic seizures in the first phase. Using a medium‐weight DCNN (mw‐DCNN) architecture, we use a preprocess phase to improve the decision‐maker method. The proposed approach was tested on the CHEG‐MIT Scalp EEG database's collected EEG signals. Result The results of the studies reveal that the mw‐DCNN algorithm produces proper classification results under various conditions. To solve the uncertainty challenge, K‐fold cross‐validation was used to assess the algorithm's repeatability at the test level, and the accuracies were evaluated in the range of 99%–100%. Conclusion The suggested structure can assist medical specialistsin analyzing epileptic seizures' EEG signals more precisely

Immunological and hematological changes in patients with hyperthyroidism or hypothyroidism

Aims: Thyroid hormones have been shown to influence the immune system and haematopoiesis. The aim of this study was to evaluate some immunological and hematological parameters in peripheral blood of hypo- or hyperthyroid women. Materials and Methods: Blood samples were collected from 50 women with hypothyroid disease, 50 women with hyperthyroid disease and a control group consisting of 50 sex - and age - matched euthyroid subjects. Thyroid function assesed according to measurent of T3, T4 and TSH levels. The complete blood count (CBC), total and differential counts of white blood cells (WBC), serum levels of immunoglobulins (IgG, IgA, IgM and IgE) and C3 and C4 complement components determined in three groups by using standard immunological and hematological methods. Results: In hyperthyroid women the mean serum concentrations of IgG (2312.4±584 mg/dl), IgA (296± 87 mg/dl) and IgE ( 301± 264 IU/ml) were significantly higher than those found in the control group (1539± 974 mg/dl, P < 0.0003; 234± 116 mg/dl, P < 0.01; 109.8±115 IU/ml, P < 0.0001, respectively) and the mean MCV was significantly lower in comparison with the euthyroid group (P < 0.05). Hypothyroid patients had higher serum IgE concentrations in comparison with the euthyroid group (179.8± 218 IU/ml vs. 109.8± 115 IU/ml; P < 0.047). The mean serum C3 concentration in hypothyroid patients was also significantly higher in comparison with the euthyroid group (138.7± 36.6 mg/ml vs. 117.8± 32.1 mg/dl; P < 0.01). In the hypothyroid group the mean eosinophil count was markedly higher in comparison with the hyperthyroid group (P < 0.06) and the mean count of RBC and the levels of some RBC-related indices, such as hematocrit and hemoglobin, were significantly lower in comparison with the euthyroid group (P < 0.05). Conclusion: These results indicate hypergammablobulinemia and lower MVC in hyperythyroid patients, and higher IgE levels, C3 levels and eosinophil count as well as anemia in hypothyroid patients

Improvement in the survival of esophageal cancer patients at cancer institute of Iran after implementation of the neo-adjuvant chemo-radiation : Retrospective cohort study

Background: Iran is a high-risk area with a poor prognosis for esophageal cancer. We conducted the present study to evaluate the survival rate of esophageal cancer after the introduction of neo-adjuvant chemo-radiation at the Cancer Institute of Iran. Method: We performed a retrospective cohort study and abstracted the data of 421 patients who referred to the Cancer Institute of Iran between 2007 and 2011. Life table and Kaplan-Meier approaches were applied to estimate 1-, 3-, and 5-year survival rates and corresponding 95% confidence intervals (CI). Multiple Cox regression model was recruited for investigating the association between 5-year survival rate and prognostic factors. Results: We found that 1-, 3-, and 5-year survival rates were 66.7%, 28.2, and 20.9%, respectively. The hazard ratio (HR) was significantly higher among the patients who has received definitive chemo-radiation therapy (Hazard ratio (HR) = 2.2, 95% confidence interval (CI): 1.1, 4.2), surgery (HR= 2.0 95% CI: 1.0, 3.7), and palliative care (HR= 4.2, 95% CI: 2.1, 1.8) compared with those who received neo-adjuvant chemo-radiation and surgery. We also found that the 5-year survival rate was doubled in the current study conducted between 2007 and 2011 (20.9%) compared with the previous one conducted between 1997 and 2006 (10.0%). Additionally, a considerable improvement was observed in 1-and 3-year survival rate of esophageal cancer at the Cancer Institute of Iran. Conclusion: Following the administration of neo-adjuvant chemo-radiation therapy, the prognosis of esophageal cancer has improved significantly at the Cancer Institute of Iran during the last decade. More data from other cancer centers and provinces of Iran are required.publishedVersionPeer reviewe