Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

The global spread of misinformation on spiders

In the internet era, the digital architecture that keeps us connected and informed may also amplify the spread of misinformation. This problem is gaining global attention, as evidence accumulates that misinformation may interfere with democratic processes and undermine collective responses to environmental and health crises1,2. In an increasingly polluted information ecosystem, understanding the factors underlying the generation and spread of misinformation is becoming a pressing scientific and societal challenge3. Here, we studied the global spread of (mis-)information on spiders using a high-resolution global database of online newspaper articles on spider–human interactions, covering stories of spider–human encounters and biting events published from 2010–20204. We found that 47% of articles contained errors and 43% were sensationalist. Moreover, we show that the flow of spider-related news occurs within a highly interconnected global network and provide evidence that sensationalism is a key factor underlying the spread of misinformation

Classification of Caesarean Section and Normal Vaginal Deliveries Using Foetal Heart Rate Signals and Advanced Machine Learning Algorithms

ABSTRACT – Background: Visual inspection of Cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% positive predictive value for the classification of pathological outcomes. This has a significant negative impact on the perinatal foetus and often results in cardio-pulmonary arrest, brain and vital organ damage, cerebral palsy, hearing, visual and cognitive defects and in severe cases, death. This paper shows that using machine learning and foetal heart rate signals provides direct information about the foetal state and helps to filter the subjective opinions of medical practitioners when used as a decision support tool. The primary aim is to provide a proof-of-concept that demonstrates how machine learning can be used to objectively determine when medical intervention, such as caesarean section, is required and help avoid preventable perinatal deaths. Methodology: This is evidenced using an open dataset that comprises 506 controls (normal virginal deliveries) and 46 cases (caesarean due to pH ≤7.05 and pathological risk). Several machine-learning algorithms are trained, and validated, using binary classifier performance measures. Results: The findings show that deep learning classification achieves Sensitivity = 94%, Specificity = 91%, Area under the Curve = 99%, F-Score = 100%, and Mean Square Error = 1%. Conclusions: The results demonstrate that machine learning significantly improves the efficiency for the detection of caesarean section and normal vaginal deliveries using foetal heart rate signals compared with obstetrician and midwife predictions and systems reported in previous studies

A Potential Role for Exosomal Translationally Controlled Tumor Protein Export in Vascular Remodeling in Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is characterized by increased proliferation and resistance to apoptosis of pulmonary vascular cells. Increased expression of translationally controlled tumor protein (TCTP), a prosurvival and antiapoptotic mediator, has recently been demonstrated in patients with heritable PAH; however, its role in the pathobiology of PAH remains unclear. Silencing of TCTP in blood outgrowth endothelial cells (BOECs) isolated from control subjects led to significant changes in morphology, cytoskeletal organization, increased apoptosis, and decreased directionality during migration. Because TCTP is also localized in extracellular vesicles, we isolated BOEC-derived extracellular vesicles (exosomes and microparticles) by sequential ultracentrifugation. BOECs isolated from patients harboring BMPR2 mutations released more exosomes than those derived from control subjects in proapoptotic conditions. Furthermore, TCTP expression was significantly higher in exosomes than in microparticles, indicating that TCTP is mainly exported via exosomes. Coculture assays demonstrated that exosomes transferred TCTP from ECs to pulmonary artery smooth muscle cells, suggesting a role for endothelial-derived TCTP in conferring proliferation and apoptotic resistance. In an experimental model of PAH, rats treated with monocrotaline demonstrated increased concentrations of TCTP in the lung and plasma. Consistent with this finding, we observed increased circulating TCTP levels in patients with idiopathic PAH compared with control subjects. Therefore, our data suggest an important role for TCTP in regulating the critical vascular cell phenotypes that have been implicated in the pathobiology of PAH. In addition, this research implicates TCTP as a potential biomarker for the onset and development of PAH.Dr. Ferrer was supported by the British Heart Foundation and SOCAP (Societat Catalana de Pneumologia). Drs. Dunmore and Ormiston were funded by the British Heart Foundation. This work was funded by awards to Professor Nick Morrell (British Heart Foundation Program Grant and the Fondation Leducq) and to Dr. Duncan Stewart (Canadian Institutes for Health Foundation Award). Infrastructure support was provided by the Cambridge National Institute for Health Research Biomedical Research Center

the European trial on Reduction of Cardiac Events with Perindopril in Stable Coronary Artery Disease Investigators. Efficacy of perindopril in reduction of cardiovascular events among patients with stable coronary artery disease: randomised, double-blind, placebo-controlled, multicentre trial (the EUROPA trial).

Background Treatment with angiotensin-converting-enzyme (ACE) inhibitors reduces the rate of cardiovascular events among patients with left-ventricular dysfunction and those at high risk of such events. We assessed whether the ACE inhibitor perindopril reduced cardiovascular risk in a low-risk population with stable coronary heart disease and no apparent heart failure. Methods We recruited patients from October, 1997, to June, 2000. 13 655 patients were registered with previous myocardial infarction (64%), angiographic evidence of coronary artery disease (61%), coronary revascularisation (55%), or a positive stress test only (5%). After a run-in period of 4 weeks, in which all patients received perindopril, 12 218 patients were randomly assigned perindopril 8 mg once daily (n=6110), or matching placebo (n=6108). The mean follow-up was 4·2 years, and the primary endpoint was cardiovascular death, myocardial infarction, or cardiac arrest. Analysis was by intention to treat. Findings Mean age of patients was 60 years (SD 9), 85% were male, 92% were taking platelet inhibitors, 62% blockers, and 58% lipid-lowering therapy. 603 (10%) placebo and 488 (8%) perindopril patients experienced the primary endpoint, which yields a 20% relative risk reduction (95% CI 9–29, p=0·0003) with perindopril. These benefits were consistent in all predefined subgroups and secondary endpoints. Perindopril was well tolerated. Interpretation Among patients with stable coronary heart disease without apparent heart failure, perindopril can significantly improve outcome. About 50 patients need to be treated for a period of 4 years to prevent one major cardiovascular event. Treatment with perindopril, on top of other preventive medications, should be considered in all patients with coronary heart disease

Efficacy of perindopril in reduction of cardiovascular events among patients with stable coronary artery disease: randomised, double-blind, placebo-controlled, multicentre trial (the EUROPA study)

BACKGROUND: Treatment with angiotensin-converting-enzyme (ACE) inhibitors reduces the rate of cardiovascular events among patients with left-ventricular dysfunction and those at high risk of such events. We assessed whether the ACE inhibitor perindopril reduced cardiovascular risk in a low-risk population with stable coronary heart disease and no apparent heart failure. METHODS: We recruited patients from October, 1997, to June, 2000. 13655 patients were registered with previous myocardial infarction (64%), angiographic evidence of coronary artery disease (61%), coronary revascularisation (55%), or a positive stress test only (5%). After a run-in period of 4 weeks, in which all patients received perindopril, 12218 patients were randomly assigned perindopril 8 mg once daily (n=6110), or matching placebo (n=6108). The mean follow-up was 4.2 years, and the primary endpoint was cardiovascular death, myocardial infarction, or cardiac arrest. Analysis was by intention to treat. FINDINGS: Mean age of patients was 60 years (SD 9), 85% were male, 92% were taking platelet inhibitors, 62% beta blockers, and 58% lipid-lowering therapy. 603 (10%) placebo and 488 (8%) perindopril patients experienced the primary endpoint, which yields a 20% relative risk reduction (95% CI 9-29, p=0.0003) with perindopril. These benefits were consistent in all predefined subgroups and secondary endpoints. Perindopril was well tolerated. INTERPRETATION: Among patients with stable coronary heart disease without apparent heart failure, perindopril can significantly improve outcome. About 50 patients need to be treated for a period of 4 years to prevent one major cardiovascular event. Treatment with perindopril, on top of other preventive medications, should be considered in all patients with coronary heart disease

The European Trial On Reduction of Cardiac Events with Perindopril in Stable Coronary Artery Disease

Background Treatment with angiotensin-converting-enzyme (ACE) inhibitors reduces the rate of cardiovascular events among patients with left-ventricular dysfunction and those at high risk of such events. We assessed whether the ACE inhibitor perindopril reduced cardiovascular risk in a low-risk population with stable coronary heart disease and no apparent heart failure. Methods We recruited patients from October, 1997, to June, 2000. 13 655 patients were registered with previous myocardial infarction (64%), angiographic evidence of coronary artery disease (61%), coronary revascularisation (55%), or a positive stress test only (5%). After a run-in period of 4 weeks, in which all patients received perindopril, 12 218 patients were randomly assigned perindopril 8 mg once daily (n=6110), or matching placebo (n=6108). The mean follow-up was 4·2 years, and the primary endpoint was cardiovascular death, myocardial infarction, or cardiac arrest. Analysis was by intention to treat. Findings Mean age of patients was 60 years (SD 9), 85% were male, 92% were taking platelet inhibitors, 62% β blockers, and 58% lipid-lowering therapy. 603 (10%) placebo and 488 (8%) perindopril patients experienced the primary endpoint, which yields a 20% relative risk reduction (95% Cl 9–29, p=0·0003) with perindopril. These benefits were consistent in all predefined subgroups and secondary endpoints. Perindopril was well tolerated. Interpretation Among patients with stable coronary heart disease without apparent heart failure, perindopril can significantly improve outcome. About 50 patients need to be treated for a period of 4 years to prevent one major cardiovascular event. Treatment with perindopril, on top of other preventive medications, should be considered in all patients with coronary heart disease