Search results for: recurrent endometriosis

Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Frikha Rim, Abdelmoula Bouayed Nouha, Rebai Tarek

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Pregnancy is a hypercoagulable state which causing a defective maternal haemostatic response and leading to thrombosis of the uteroplacental vasculature, that might cause pregnancy complications as recurrent pregnancy loss (RPL). Since heritable Thrombophilic defects are associated with increased thrombosis, their prevalence was evaluated in patients with special emphasis on combinations of the above pathologies. Especially, Factor V Leiden (FVL) G1691A, methylene tetra hydro folate reductase (MTHFR) C677T, and factor II (FII) G20210A mutations are three important causes of thrombophilia, which might be related to recurrent pregnancy loss (RPL). In this study we evaluated the presence of these three mutations [factor V Leiden (FVL), prothrombin G20210A (PTG) and methylenetetrahydrofolate reductase (MTHFR) C677T] amongst 35 Tunisian women with more than 2 miscarriages, referred to our genetic counseling. DNA was extracted from peripheral blood samples and PCR-RFLP was performed for the molecular diagnosis of each mutation. Factor V Leiden and Prothrombin mutation were detected respectively in 5.7% and 2.9% of women with particular history of early fetal loss and thrombotic events. Despites the luck of strength of this study, we insist that testing for the most inherited thrombophilia (FVL and FII mutation) should be performed in women with RPL in the context of thrombotic events. Multi-centre collaboration is necessary to clarify the real impact of thrombotic molecular defects on the pregnancy outcome, to ascertain the effect of thrombophilia on recurrent pregnancy loss and then to evaluate the appropriate therapeutic approach.

Keywords: thrombophilia, recurrent pregnancy loss, factor V Leiden, prothrombin G20210A, methylene tetra hydro folate reductase

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Thippharat Wongsilarat, Parichat tuntilanon, Chonlakan Prataksitorn

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Recurrent adverse drug reactions are harmful to patients with mild to fatal illnesses, and affect not only patients but also their relatives, and organizations. To compare safe use of medicine among patients before and after using the recurrent adverse drug reaction prevention program . Quasi-experimental research with the target population of 598 patients with drug allergy history. Data were collected through an observation form tested for its validity by three experts (IOC = 0.87), and analyzed with a descriptive statistic (percentage). The research was conducted jointly with a multidisciplinary team to analyze and determine the weak points and strong points in the recurrent adverse drug reaction prevention system during the past three years, and 546, 329, and 498 incidences, respectively, were found. Of these, 379, 279, and 302 incidences, or 69.4; 84.80; and 60.64 percent of the patients with drug allergy history, respectively, were found to have caused by incomplete warning system. In addition, differences in practice in caring for patients with drug allergy history were found that did not cover all the steps of the patient care process, especially a lack of repeated checking, and a lack of communication between the multidisciplinary team members. Therefore, the recurrent adverse drug reaction prevention program was developed with complete warning points in the information technology system, the repeated checking step, and communication among related multidisciplinary team members starting from the hospital identity card room, patient history recording officers, nurses, physicians who prescribe the drugs, and pharmacists. Including in the system were surveillance, nursing, recording, and linking the data to referring units. There were also training concerning adverse drug reactions by pharmacists, monthly meetings to explain the process to practice personnel, creating safety culture, random checking of practice, motivational encouragement, supervising, controlling, following up, and evaluating the practice. The rate of prescribing drugs to which patients were allergic per 1,000 prescriptions was 0.08, and the incidence rate of recurrent drug reaction per 1,000 prescriptions was 0. Surveillance of recurrent adverse drug reactions covering all service providing points can ensure safe use of medicine for patients.

Keywords: recurrent drug, adverse reaction, safety, use of medicine

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Barbara Torres Rives

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Uveitis. Non-infectious anterior uveitis is a polygenic inflammatory eye disease, and it is suggested that mediated processes by the immune system (autoimmune or not) are the main mechanisms proposed in the pathogenesis of this type of uveitis. A relationship between infectious processes, digestive disorders, and a dysbiosis of the microbiome was recently described. In addition, alterations in the immune response associated with the initiation and progression of the disease have been described. Objective: The aim of this study was to identify factors related to the immune system associated with complicated non-infectious anterior uveitis. Methods: A cross-sectional observational analytical study was carried out. The universe consisted of all patients attending the ocular inflammation service of the Cuban Institute of Ophthalmology Ramón Pando Ferrer. The sample consisted of 213 patients diagnosed with non-infectious anterior uveitis. Results: Of the 213 patients with non-infectious anterior uveitis, the development of ophthalmologic complications predominated 56.3% (p=0.0094). In patients with complications was more frequent the presence of human leukocyte antigen-B27 allele (49.2%) (p<0.0001), decreased immunoglobulin G (24.2%, p=0.0124), increased immunoglobulin A (14.2%, p=0.0024), history of recurrent sepsis (59.2%, p=0.0018), recurrent respiratory infections (44.2%, p=0.0003), digestive alterations (40%, p=0.0013) and spondyloarthropathies (30%, p=0.0314). By logistic regression, it was observed that, for each completed year, the elevated risk for developing complicated non-infectious anterior uveitis in human leukocyte antigen-B27 allele positive patients (OR: 4.22, p=0.000), Conclusions: The control of recurrent sepsis at mucosal level and immunomodulation could prevent complications in non-infectious anterior uveitis. Therefore, the microbiome becomes the target of treatment and prevention of complications in non-infectious anterior uveitis.

Keywords: non-infectious anterior uveitis, immune system disorders, recurrent mucosal infections, microbiome

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Authors: Ae Ra Han, Taek Hoo Lee, Sun Zoo Kim, Hwa Young Lee

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Introduction: Ovarian endometrioma is one of the important causes of poor ovarian reserve and up to half of them have recurred. However, the treatment for recurrence prevention has limited efficiency and repeated surgical management makes worsen the ovarian reserve. To find better management for recurrence prevention, we investigated risk factors and biomarkers for the recurrence of ovarian endometrioma. Methods: The medical records of women with the history of surgical dissection for ovarian endometrioma were collected. After exclusion of the cases with concurrent hysterectomy, been menopaused during follow-up, incomplete medical record, and loss of follow-up, a total of 134 women were enrolled. Immunohistochemical staining for progesterone receptor isoform B (PR-B) and nuclear factor kappa B (NFκB) was done with the fixed tissue blocks of their endometriomas which were collected at the time of surgery. Results: Severity of dysmenorrhea and co-existence of adenomyosis had significant correlation with recurrence of endometrioma. Increased PR-B (P = .041) and decreased NFκB (P = .036) immunoreactivity were found in recurrent group. Serum CA-125 level at the time of recurrence was higher than the highest level of CA-125 during follow-up in unrecurred group (55.6 vs. 21.3 U/mL, P = .014). Conclusion: We found that the severity of dysmenorrhea and coexistence of adenomyosis are risk factors for recurrence of ovarian endometrioma, and serial follow-up of CA-125 is effective to detect and prevent the recurrence. However, to determine the possibility of immunoreactivity of PR-B and NFκB as biomarkers for ovarian endometrioma, further studies of various races and large numbers with prospective design are needed.

Keywords: endometriosis, recurrence, biomarker, risk factor

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Authors: Radwa El Shorbagy, Alaa El Din Balbaa, Khaled Ayad, Waleed Reda

Abstract:

Ankle sprain is a common lower limb injury that is complicated by high recurrence rate. The cause of recurrence is not clear; however, changes in motor control have been postulated.Objective: to determine the contribution of proximal hip strategy to dynamic posture control in patients with recurrent ankle sprain. Methods:Fifteen subjects with recurrent ankle sprain (Group A) and fifteen healthy control subjects (Group B) participated in this study. Abductor-adductor as well as flexor-extensor hip musculature control was abolished by fatigue using the Biodex Isokinatic System. Dynamic posture control was measured before and after fatigue by the Biodex Balance System. Results: Repeated measures MANOVA was used to compare within group differences. In group A fatiguing of hip muscles (flexors-extensors and abductors-adductors) lowered overall stability index (OASI), anteroposterior stability index (APSI) and mediolateral stability index (MLSI) significantly (p=0.00) whereas; in group B fatiguing of hip flexors-extensors lowered significantly OASI and APSI only (p= 0.017, 0.010; respectively) while fatiguing of hip abductors-adductors has no significant effect on these variables. Conclusion: fatiguing of hip muscles has a significant deleterious effect on dynamic posture control in patient with recurrent ankle sprain indicating their increased dependence on hip strategy.

Keywords: ankle sprain, fatigue hip muscles, dynamic balance, ankle sprain

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Authors: Shibo Wei, Ting Jiang

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Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

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Authors: Khaled Alabduljabbar

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Background: Benign, isolated, recurrent sixth nerve palsy is very rare in children. Here we report a case of recurrent abducens nerve palsy with no obvious etiology. It is a diagnosis of exclusion. A recurrent benign form of 6th nerve palsy, a rarer still palsy, has been described in the literature, and it is of most likely secondary to inflammatory causes, e.g, following viral and bacterial infections. Purpose: To present a case of 14 months old girl with recurrent attacks of isolated left sixth cranial nerve palsy following upper respiratory tract infection. Observation: The patient presented to opthalmology clinic with sudden onset of inward deviation (esotropia) of the left eye with a compensatory left face turn one week following signs of upper respiratory tract infection. Ophthalmological examination revealed large angle esotropia of the left eye in primary position, with complete limitation of abduction of the left eye, no palpebral fissure changes, and abnormal position of the head (left face turn). Visual acuity was normal, and no significant refractive error on cycloplegic refraction for her age. Fundus examination was normal with no evidence of papilledema. There was no relative afferent pupillary defect (RAPD) and no anisocoria. Past medical history and family history were unremarkable, with no history of convulsion attacks or head trauma. Additional workout include CBC. Erythrocyte sedimentation rate, Urgent magnetic resonance imaging (MRI), and angiography of the brain were performed and demonstrated the absence of intracranial and orbital lesions. Referral to pediatric neurologist was also done and concluded no significant finding. The patient showed improvement of the left sixth cranial nerve palsy and left face turn over a period of two months. Seven months since the first attack, she experienced a recurrent attack of left eye esotropia with left face turn concurrent with URTI. The rest of eye examination was again unremarkable. CT scan and MRI scan of brain and orbit were performed and showed only signs of sinusitis with no intracranial pathology. The palsy resolved spontaneously within two months. A third episode of left 6th nerve palsy occurred 6 months later, whichrecovered over one month. Examination and neuroimagingwere unremarkable. A diagnosis of benign recurrent left 6th cranial nerve palsy was made. Conclusion: Benign sixth cranial nerve palsy is always a diagnosis of exclusion given the more serious and life-threatening alternative causes. It seems to have a good prognosis with only supportive measures. The likelihood of benign 6th cranial nerve palsy to resolve completely and spontaneously is high. Observation for at least 6 months without intervention is advisable.

Keywords: 6th nerve pasy, abducens nerve pasy, recurrent nerve palsy, cranial nerve palsy

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Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Radwa Elshorbagy, Alaa Elden Balbaa, Khaled Ayad, Waleed Reda

Abstract:

Introduction: Ankle sprain is a common lower limb injury that is complicated by high recurrence rate. The cause of recurrence is not clear; however, changes in motor control have been postulated. Objective: to determine the contribution of proximal hip strategy to dynamic postural control in patients with recurrent ankle sprain. Methods: Fifteen subjects with recurrent ankle sprain (group A) and fifteen healthy control subjects (group B) participated in this study. Abductor-adductors as well as flexor-extensor hip musculatures control was abolished by fatigue using the Biodex Isokinetic System. Dynamic postural control was measured before and after fatigue by the Biodex Balance System. Results: Repeated measures MANOVA was used to compare between and within group differences, in group A fatiguing of hip muscles (flexors-extensors and abductors-adductors) increased overall stability index (OASI), anteroposterior stability index (APSI) and mediolateral stability index (MLSI) significantly (p=0.00) whereas; in group B fatiguing of hip flexors-extensors increased significantly OASI and APSI only (p= 0.017, 0.010; respectively) while fatiguing of hip abductors-adductors has no significant effect on these variables. Moreover, patients with ankle sprain had significantly lower dynamic balance after hip muscles fatigue compared to the control group. Specifically, after hip flexor-extensor fatigue, the OASI, APSI and MLSI were increased significantly than those of the control values (p= 0.002, 0.011, and 0.003, respectively) whereas fatiguing of hip abductors-adductors increased significantly in OASI and APSI only (p=0.012, 0.026, respectively). Conclusion: To maintain dynamic balance, patients with recurrent ankle sprain seem to rely more on the hip strategy. This means that those patients depend on a top to down instead of down to top strategy clinical relevance: patients with recurrent ankle sprain less efficient in maintaining the dynamic postural control due to the change in motor strategies. Indicating that health care providers and rehabilitation specialists should treat CAI as a global/central and not just as a simple local or peripheral injury.

Keywords: hip strategy, ankle strategy, postural control, dynamic balance

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Authors: Radwa El Shorbagy, Alaa El Din Balbaa, Khaled Ayad, Waleed Reda

Abstract:

Introduction: Ankle sprain is a common lower limb injury that is complicated by high recurrence rate. The cause of recurrence is not clear; however, changes in motor control have been postulated. Objective: to determine the contribution of proximal hip strategy to dynamic postural control in patients with recurrent ankle sprain. Methods: Fifteen subjects with recurrent ankle sprain (group A) and fifteen healthy control subjects (group B) participated in this study. Abductor-adductors as well as flexor-extensor hip musculatures control was abolished by fatigue using the Biodex Isokinetic System. Dynamic postural control was measured before and after fatigue by the Biodex Balance System Results: Repeated measures MANOVA was used to compare between and within group differences, In group A fatiguing of hip muscles (flexors-extensors and abductors-adductors) increased overall stability index (OASI), anteroposterior stability index (APSI) and mediolateral stability index (MLSI) significantly (p= 0.00) whereas; in group B fatiguing of hip flexors-extensors increased significantly OASI and APSI only (p= 0.017, 0.010; respectively) while fatiguing of hip abductors-adductors has no significant effect on these variables. Moreover, patients with ankle sprain had significantly lower dynamic balance after hip muscles fatigue compared to the control group. Specifically, after hip flexor-extensor fatigue, the OASI, APSI and MLSI were increased significantly than those of the control values (p= 0.002, 0.011, and 0.003, respectively) whereas fatiguing of hip abductors-adductors increased significantly in OASI and APSI only (p=0.012, 0.026, respectively). Conclusion: To maintain dynamic balance, patients with recurrent ankle sprain seem to relay more on the hip strategy. This means that those patients depend on a top to down instead of down to top strategy clinical relevance: patients with recurrent ankle sprain less efficient in maintaining the dynamic postural control due to the change in motor strategies. Indicating that health care providers and rehabilitation specialists should treat CAI as a global/central and not just as a simple local or peripheral injury.

Keywords: ankle sprain, fatigue hip muscles, dynamic balance

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Authors: Harshadkumar Rajgor, Jeff Butterworth

Abstract:

Background: Barretts oesophagus increases the risk of developing oesophageal adenocarcinoma. Over the last 40 years, there has been a 6 fold increase in the incidence of oesophageal adenocarcinoma in the western world and the incidence rates are increasing at a greater rate than cancers of the colon, breast and lung. Endoscopic mucosal resection (EMR) is a relatively new technique being used by 2 centres in the greater midlands cancer network. EMR can be used for curative or staging purposes, for high-grade dysplasia’s and T1 tumours of the oesophagus. EMR is also suitable for those who are deemed high risk for oesophagectomy. EMR has a recurrence rate of 21% according to the Wiesbaden data. Method: A retrospective study of prospectively collected data was carried out involving 24 patients who had EMR for curative or staging purposes. Complications of residual or recurrent disease following EMR that required further treatment were investigated. Results: In 54% of cases residual or recurrent disease was suspected. 96% of patients were given clear and concise information regarding their diagnosis of high-grade dysplasia or T1 tumours. All 24 patients consulted the same specialist healthcare team. Conclusion: EMR is a safe and effective treatment for patients who have high-grade dysplasia and T1NO tumours. In 54% of cases residual or recurrent disease was suspected. Initially, only single resections were undertaken. Multiple resections are now being carried out to reduce the risk of recurrence. Complications from EMR remain low in this series and consisted of a single episode of post procedural bleeding.

Keywords: endoscopic mucosal resection, oesophageal dysplasia, T1 tumours, cancer network

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Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

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Authors: Radwa Talaat Mohammed El-Shorbagy, Alaa El-Din Balbaa, Khaled Ayad, Waleed Red

Abstract:

Introduction: Ankle sprain is a common lower limb injury that is complicated by high recurrence rate. The cause of recurrence is not clear; however, changes in motor control have been postulated. Objective: To determine the contribution of proximal hip strategy to dynamic balance control in patients with recurrent ankle sprain. Methods: Fifteen subjects with recurrent ankle sprain (group A) and fifteen healthy control subjects (group B) participated in this study. Abductor-adductors as well as flexor-extensor hip musculatures control was abolished by fatigue using the Biodex Isokinetic system. Dynamic balance was measured before and after fatigue by the Biodex Balance system Results: Repeated measures MANOVA was used to compare between and within group differences. In group A fatiguing of hip muscles (flexors-extensors and abductors-adductors) increased overall stability index (OASI), anteroposterior stability index (APSI) and mediolateral stability index (MLSI) significantly (p=0.00) whereas; in group B fatiguing of hip flexors-extensors increased significantly OASI and APSI only (p= 0.017, 0.010; respectively) while fatiguing of hip abductors-adductors has no significant effect on these variables. Moreover, patients with ankle sprain had significantly lower dynamic balance after hip muscles fatigue compared to the control group. Specifically, after hip flexor-extensor fatigue, the OASI, APSI and MLSI were increased significantly than those of the control values (p=0.002, 0.011, and 0.003, respectively) whereas fatiguing of hip abductors-adductors increased significantly in OASI and APSI only (p=0.012, 0.026, respectively). Conclusion: To maintain dynamic balance, patients with recurrent ankle sprain seem to relay more on the hip strategy.

Keywords: ankle sprain, hip muscles fatigue, dynamic balance

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Authors: Pius Marthin, Nihal Ata Tutkun

Abstract:

Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Luksanaporn Krungkraipetch

Abstract:

Pterygium is a frequent ocular surface lesion that begins in the limbal conjunctiva within the palpebral fissure and spreads to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a wing-like aspect. Indications for surgery, in decreasing order of significance, are growth over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and esthetic concerns. The aim of this study is twofold: first, to determine the frequency of pterygium recurrence after surgery at the mentioned hospital, and second, to identify the factors that influence the recurrence of pterygium. The research design is a retrospective examination of 164 patient samples in an eastern Thai university hospital (Code 13766). Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium, and for factor analysis, the inferential statistics chi-square and ANOVA are utilized. Twenty-four of the 164 patients who underwent surgery exhibited recurrent pterygium. Consequently, the incidence of recurrent pterygium after surgery was 14.6%. There were an equal number of men and women present. The participants' ages ranged from 41 to 60 years (62, 8 percent). According to the findings, the majority of patients were female (60.4%), over the age of 60 (51.2%), did not live near the beach (83.5%), did not have an underlying disease (92.1%), and 95.7% did not have any other eye problems. Gender (X² = 1.26, p = .289), age (X² = 5.86, p = .119), an address near the sea (X² = 3.30, p = .081)), underlying disease (X² = 0.54, p = .694), and eye disease (X² = 0.00, p = 1.00) had no effect on pterygium recurrence. Recurrences occurred in 79.1% of all surgical procedures and 11.6% of all patients using the bare sclera technique. The recurrence rate for conjunctival autografts was 20.9% for all procedures and 3.0% for all participants. Mitomycin-C and amniotic membrane transplant techniques had no recurrence following surgery. Comparing the surgeries done on people with recurrent pterygium did not show anything important (F = 1.13, p = 0.339). In conclusion, the prevalence of pterygium recurrence following pterygium, 14.6%, does not differ from earlier research. Underlying disease, other eye conditions, and surgical procedures such as pterygium recurrence are unaffected by pterygium surgery.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

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Authors: Horesh Reinman Netta

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Objectives: To examine the relationship between stressful life events and recurrent major depressive disorders Methods: Three groups of 50 subjects were assessed. One group had a recurrent major depressive disorder with melancholic features; the second group met the criteria for borderline personality disorder, and the third consisted of healthy controls. The Structured Clinical Interview for AXIS I DSM-IV Disorders sand the Structured Clinical Interview for AXIS II DSM-IV Disorders were used for diagnosis. The Israel Psychiatric Epidemiology Research Interview (IPERI) Life Event Scale and the Coddington Life Events Schedule (CLES) were used to measure life events which were confirmed with a confirmatory semi-structured interview. The Beck Depression Inventory and the Satisfaction from Life scales were also administered. Results : The total number of loss-related events in childhood and in the year preceding the first episode was significantly higher in the affective disorder group than in the two control groups. Total number of LE, uncontrolled and independent events were also more common in the depressed patients in the year preceding the first episode. No category of SLE was differentiated among any of the three groups during any period of time following the first depressive episode. Conclusions: SLE play an important role in the onset of affective disorders. There appear to be specific kinds of SLE occurring in childhood and in the year preceding a first episode that have particular significance. SLE may have a lesser role in the maintenance of this illness.

Keywords: modd dosorders, recurrent depression, stress, life events

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

Procedia PDF Downloads 36

Authors: Rim Frikha, Nouha Bouayed, Afifa Sellami, Nozha Chakroun, Salima Daoud, Leila Keskes, Tarek Rebai

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Introduction: Recurrent pregnancy loss (RPL) defined as two or more pregnancy losses, is a serious clinical problem. Methylene-tetrahydro-folate-reductase (MTHFR) polymorphisms, commonly the variant C677T is recognized as an inherited thrombophilia which might affect embryonic development and pregnancy success and cause pregnancy complications as RPL. Material and Methods DNA was extracted from peripheral blood samples and PCR-RFLP was performed for the molecular diagnosis of the C677T MTHFR polymorphism among 70 patients (35 couples) with more than 2 fetal losses. Aims and Objective: The aim of this study is to determine the frequency of MTHFR C677T among Tunisian couples with RPL and to critically analyze the available literature on the importance of MTHFR polymorphism testing in the management of RPL. Result and comments: No C677T mutation was detected in the carriers of RPL. This result would be related to sample size and to different criteria (number of abortion), - The association between MTHFR polymorphisms and pregnancy complications has been reported but with controversial results. - A lack of evidence for MTHFR polymorphism testing previously recommended by ACMG (American College of Medical medicine). Our study highlights the importance of screening of MTHFR polymorphism since the real impact of such thrombotic molecular defect on the pregnancy outcome is evident. - Folic supplementation of these patients during pregnancy can prevent such complications and lead to a successful pregnancy outcome.

Keywords: methylenetetrahydrofolate reductase, C677T, recurrent pregnancy loss, genetic testing

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Authors: Lee Rui, Rajeev Ramachandran

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The approach to recurrent fevers in the paediatric or adolescent age group is not a straightforward one. Causes range from infectious diseases to rheumatological conditions to endocrinopathies, and are usually accompanied by weight loss rather than weight gain. We present an interesting case of a 16-year-old girl brought by her mother to the General Pediatrics Clinic for concerns of recurrent fever paired with significant weight gain over 1.5 years, with no identifiable cause found despite extensive work-up by specialists ranging from Rheumatologists to Oncologists. This case provides a learning opportunity on the approach to weight gain paired with persistent fevers in a paediatric population, one which is not commonly encountered and prompts further evaluation and consideration of less common diagnoses. In a span of 2 years, the girl’s weight had increased from 55 kg at 13 years old (75th centile) to 73.9 kg at 16 years old (>97th centile). About 1 year into her rapid weight gain, she started developing recurrent fevers of documented temperatures > 37.5 – 38.6 every 2-3 days, resulting in school absenteeism when she was sent home after temperature-taking in school found her to be febrile. The rapid onset of weight gain paired with unexplained fevers prompted the treating physician to consider the diagnosis of ROHHAD syndrome. Rapid onset obesity with hypoventilation, hypothalamic dysfunction and autonomic dysregulation (ROHHAD) syndrome is a rare disorder first described in 2007. It is characterized by dysfunction of the autonomic and endocrine system, characterized by hyperphagia and rapid-onset weight gain. This rapid weight gain is classically followed by hypothalamic manifestations with neuroendocrine deficiencies, hypo-ventilatory breathing abnormalities, and autonomic dysregulation. ROHHAD is challenging to diagnose with and diagnosis is made based mostly on clinical judgement. However if truly diagnosed, the condition is characterized by high morbidity and mortality rates. Early recognition of sleep disorders breathing and targeted therapeutic interventions helps limit morbidity and mortality associated with ROHHAD syndrome. This case poses an interesting diagnostic challenge and a diagnosis of ROHHAD has to be considered, given the serious complications that can come with disease progression while conditions such as Munchausen’s or drug fever remain as diagnoses of exclusion until we have exhausted all other possible conditions.

Keywords: pediatrics, endocrine, weight gain, recurrent fever, adolescent

Procedia PDF Downloads 71

Authors: Luksanaporn Krungkraipetch

Abstract:

A pterygium is an eye surface lesion that begins in the limbal conjunctiva and progresses to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a distinctive wing-like aspect. Indications for surgery, in decreasing order of significance, are grown over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and aesthetic concerns. Recurrent pterygium results in the loss of time, the expense of therapy, and the potential for vision impairment. The objective of this study is to find out how often the recurrence of pterygium after surgery occurs, what effect the surgery technique has, and what causes them to come back in people with pterygium. Materials and Methods: Observational case control in retrospect: the study involves a retrospective analysis of 164 patient samples. Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium. For factor analysis, the inferential statistics odds ratio (OR) and 95% confidence interval (CI) ANOVA are utilized. A p-value of 0.05 was deemed statistically important. Results: The majority of patients, according to the results, were female (60.4%). Twenty-four of the 164 (14.6%) patients who underwent surgery exhibited recurrent pterygium. The average age is 55.33 years old. Postoperative recurrence was reported in 19 cases (79.3%) of bare sclera techniques and five cases (20.8%) of conjunctival autograft techniques. The recurrence interval is 10.25 months, with the most common (54.17 percent) being 12 months. In 91.67 percent of cases, all follow-ups are successful. The most common recurrence level is 1 (25%). A surgical complication is a subconjunctival hemorrhage (33.33 percent). Comparing the surgeries done on people with recurrent pterygium didn't show anything important (F = 1.13, p = 0.339). Age significantly affected the recurrence of pterygium (95% CI, 6.79-63.56; OR = 20.78, P 0.001). Conclusion: This study discovered a 14.6% rate of pterygium recurrence after pterygium surgery. Across all surgeries and patients, the rate of recurrence was four times higher with the bare sclera method than with conjunctival autograft. The researchers advise selecting a more conventional surgical technique to avoid a recurrence.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

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Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

Procedia PDF Downloads 93