2,514 results match your criteria error grid

Penalty weighted glucose prediction models could lead to better clinically usage.

Comput Biol Med 2021 Sep 15;138:104865. Epub 2021 Sep 15.

Department of Health Science and Technology, Aalborg University, Denmark.

Background And Objective: Numerous attempts to predict glucose value from continuous glucose monitors (CGM) have been published. However, there is a lack of proper analysis and modeling of penalty for errors in different glycemic ranges. The aim of this study was to investigate the potential for developing glucose prediction models with focus on the clinical aspects. Read More

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September 2021

Diagnosis of Pediatric Pneumonia with Ensemble of Deep Convolutional Neural Networks in Chest X-Ray Images.

Arab J Sci Eng 2021 Sep 12:1-17. Epub 2021 Sep 12.

Department of Computer Engineering, Faculty of Engineering and Architecture, Kirikkale University, Yahsihan, Kirikkale Turkey.

Pneumonia is a fatal disease that appears in the lungs and is caused by viral or bacterial infection. Diagnosis of pneumonia in chest X-ray images can be difficult and error-prone because of its similarity with other infections in the lungs. The aim of this study is to develop a computer-aided pneumonia detection system to facilitate the diagnosis decision process. Read More

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September 2021

Exploring the attitudes of Millennials and Generation Xers toward ridesourcing services.

Transportation (Amst) 2021 Sep 13:1-35. Epub 2021 Sep 13.

Department of Civil and Environmental Engineering, Florida International University, 10555 W. Flagler Street, EC3725, Miami, FL 33174 USA.

This paper presents a study investigating the potential market of ridesourcing services, with a focus on the attitudinal and preferential differences between Millennials and Generation Xers. Data obtained from a stated preference survey were utilized, where the respondents were asked to choose between a conventional mode (private vehicle driver, transit, or private vehicle passenger) and ridesourcing modes (exclusive ride and shared ride). Error component nested logit models were developed for Generation Xers and Millennials, respectively. Read More

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September 2021

Device profile of the Eversense continuous glucose monitoring system for glycaemic control in type-1 diabetes: overview of its safety and efficacy.

Expert Rev Med Devices 2021 Sep 16. Epub 2021 Sep 16.

Senseonics, Inc., Germantown, Maryland, US.

Introduction: Continuous glucose monitoring (CGM) systems offer real-time data to facilitate diabetes management. The novel Eversense CGM has been approved in Europe and the US. The unique characteristics are the fully implantable sensor and the sensor life up to 180 days. Read More

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September 2021

Reanalysis of the association between reduction in long-term PM concentrations and improved life expectancy.

Environ Health 2021 09 13;20(1):102. Epub 2021 Sep 13.

Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.

Background: Much of the current evidence of associations between long-term PM and health outcomes relies on national or regional analyses using exposures derived directly from regulatory monitoring data. These findings could be affected by limited spatial coverage of monitoring data, particularly for time periods before spatially extensive monitoring began in the late 1990s. For instance, Pope et al. Read More

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September 2021

Toward new multi-wavelets: associated filters and algorithms. Part I: theoretical framework and investigation of biomedical signals, ECG, and coronavirus cases.

Soft comput 2021 Sep 6:1-21. Epub 2021 Sep 6.

LATIS, Laboratory of Advanced Technology, and Intelligent Systems, Université de Sousse, Ecole Nationale d'Ingénieurs de Sousse, 4023 Sousse, Tunisie.

Biosignals are nowadays important subjects for scientific researches from both theory, and applications, especially, with the appearance of new pandemics threatening the humanity such as the new coronavirus. One aim in the present work is to prove that wavelets may be a successful machinery to understand such phenomena by applying a step forward extension of wavelets to multi-wavelets. We proposed in a first step to improve multi-wavelet notion by constructing more general families using independent components for multi-scaling and multi-wavelet mother functions. Read More

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September 2021

Errors of programming and ownership of the robot concept made by trainee kindergarten teachers during an induction training.

Educ Inf Technol (Dordr) 2021 Sep 6:1-21. Epub 2021 Sep 6.

Departament of Linguistic and Literary Education, and Teaching and Learning of Experimental Sciences and Mathematics, Universitat de Barcelona, Barcelona, Spain.

Computational thinking in the educational environment has awaken a rising interest, having been included as part of the curricula from the very beginnings of education. Programmable robots have become a valuable positive resource in order to succeed in the development of computational thinking, demanding proper training from kindergarten teachers and trainees in order to be able to teach robotic programming. This article has the purpose to 1) identify the frequent errors made by trainee kindergarten teachers when solving a series of robotic problems in a computational thinking module, which develops in the course of Didactics of Mathematics and 2) determine the level of comprehension of the robot concept acquired by the trainees when solving robotics problems. Read More

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September 2021

Solder Joint Reliability Risk Estimation by AI-Assisted Simulation Framework with Genetic Algorithm to Optimize the Initial Parameters for AI Models.

Materials (Basel) 2021 Aug 26;14(17). Epub 2021 Aug 26.

Department of Electronic Components, Technology, and Materials, Delft University of Technology, 2628 CD Delft, The Netherlands.

Solder joint fatigue is one of the critical failure modes in ball-grid array packaging. Because the reliability test is time-consuming and geometrical/material nonlinearities are required for the physics-driven model, the AI-assisted simulation framework is developed to establish the risk estimation capability against the design and process parameters. Due to the time-dependent and nonlinear characteristics of the solder joint fatigue failure, this research follows the AI-assisted simulation framework and builds the non-sequential artificial neural network (ANN) and sequential recurrent neural network (RNN) architectures. Read More

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Quantifying changes in ultrasound tongue-shape pre- and post-intervention in speakers with submucous cleft palate: an illustrative case study.

Clin Linguist Phon 2021 Sep 8:1-19. Epub 2021 Sep 8.

Clinical Audiology, Speech and Language Research Centre, Queen Margaret University, Edinburgh, Scotland.

Ultrasound Tongue Imaging is increasingly used during assessment and treatment of speech sound disorders. Recent literature has shown that ultrasound is also useful for the quantitative analysis of a wide range of speech errors. So far, the compensatory articulations of speakers with cleft palate have only been analysed qualitatively. Read More

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September 2021

Incorporating Glucose Variability into Glucose Forecasting Accuracy Assessment Using the New Glucose Variability Impact Index and the Prediction Consistency Index: An LSTM Case Example.

J Diabetes Sci Technol 2021 Sep 7:19322968211042621. Epub 2021 Sep 7.

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.

Background: In this work, we developed glucose forecasting algorithms trained and evaluated on a large dataset of free-living people with type 1 diabetes (T1D) using closed-loop (CL) and sensor-augmented pump (SAP) therapies; and we demonstrate how glucose variability impacts accuracy. We introduce the glucose variability impact index (GVII) and the glucose prediction consistency index (GPCI) to assess the accuracy of prediction algorithms.

Methods: A long-short-term-memory (LSTM) neural network was designed to predict glucose up to 60 minutes in the future using continuous glucose measurements and insulin data collected from 175 people with T1D (41,318 days) and evaluated on 75 people (11,333 days) from the Tidepool Big Data Donation Dataset. Read More

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September 2021

Post-Market Surveillance of a Blood Glucose Test Strip Demonstrates No Evidence of Interference on Clinical Accuracy in a Large Cohort of People with Type 1 or Type 2 Diabetes.

J Diabetes Sci Technol 2021 Sep 4:19322968211042352. Epub 2021 Sep 4.

LifeScan Scotland Ltd, Inverness, UK.

Background: Regulations and industry guidance relating to testing for interference in blood glucose monitoring (BGM) systems continue to focus on in vitro laboratory bench tests. Post-market surveillance (PMS) in a clinical setting allows for BGM accuracy assessments to evaluate the impact of real-world exposure to polypharmacy in people with diabetes. This study evaluated the OneTouch Select Plus® BGM test-strip accuracy with respect to polypharmacy using a clinical registry dataset. Read More

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September 2021

Teaching Individuals with Autism Problem-Solving Skills for Resolving Social Conflicts.

Behav Anal Pract 2021 Aug 30:1-14. Epub 2021 Aug 30.

Halo Behavioral Health, Valley Village, California USA.

Resolving social conflicts is a complex skill that involves consideration of the group when selecting conflict solutions. Individuals with autism spectrum disorder (ASD) often have difficulty resolving social conflicts, yet this skill is important for successful social interaction, maintenance of relationships, and functional integration into society. This study used a nonconcurrent multiple baseline across participants design to assess the efficacy of a problem-solving training and generalization of problem solving to naturally occurring untrained social conflicts. Read More

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Optimal futures hedging strategies based on an improved kernel density estimation method.

Soft comput 2021 Sep 1:1-15. Epub 2021 Sep 1.

Business School, University of Jinan, Jinan, 250022 China.

In this paper, we study the hedging effectiveness of crude oil futures on the basis of the lower partial moments (LPMs). An improved kernel density estimation method is proposed to estimate the optimal hedge ratio. We investigate crude oil price hedging by contributing to the literature in the following twofold: First, unlike the existing studies which focus on univariate kernel density method, we use bivariate kernel density to calculate the estimated LPMs, wherein the two bandwidths of the bivariate kernel density are not limited to the same, which is our main innovation point. Read More

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September 2021

Prediction of face age progression with generative adversarial networks.

Multimed Tools Appl 2021 Aug 28:1-25. Epub 2021 Aug 28.

Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab 147001 India.

Face age progression, goals to alter the individual's face from a given face image to predict the future appearance of that image. In today's world that demands more security and a touchless unique identification system, face aging attains tremendous attention. The existing face age progression approaches have the key problem of unnatural modifications of facial attributes due to insufficient prior knowledge of input images and nearly visual artifacts in the generated output. Read More

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Technical note: A fast and accurate analytical dose calculation algorithm for I seed-loaded stent applications.

Med Phys 2021 Sep 4. Epub 2021 Sep 4.

Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina, USA.

Purpose: The safety and clinical efficacy of I seed-loaded stent for the treatment of portal vein tumor thrombosis (PVTT) have been shown. Accurate and fast dose calculation of the I seeds with the presence of the stent is necessary for the plan optimization and evaluation. However, the dosimetric characteristics of the seed-loaded stents remain unclear and there is no fast dose calculation technique available. Read More

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September 2021

Clinical evaluation of a wearable sensor for mobile monitoring of respiratory rate on hospital wards.

J Clin Monit Comput 2021 Sep 2. Epub 2021 Sep 2.

Department of Anesthesia, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

A wireless and wearable system was recently developed for mobile monitoring of respiratory rate (RR). The present study was designed to compare RR mobile measurements with reference capnographic measurements on a medical-surgical ward. The wearable sensor measures impedance variations of the chest from two thoracic and one abdominal electrode. Read More

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September 2021

A Comparison of Deep Learning Techniques for Arterial Blood Pressure Prediction.

Cognit Comput 2021 Aug 27:1-22. Epub 2021 Aug 27.

DET - Department of Electronics and Telecommunications, Politecnico Di Torino, Turin, Italy.

Continuous vital signal monitoring is becoming more relevant in preventing diseases that afflict a large part of the world's population; for this reason, healthcare equipment should be easy to wear and simple to use. Non-intrusive and non-invasive detection methods are a basic requirement for wearable medical devices, especially when these are used in sports applications or by the elderly for self-monitoring. Arterial blood pressure (ABP) is an essential physiological parameter for health monitoring. Read More

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Psychometric Properties of the Coronavirus Stress Measure with Malaysian Young Adults: Association with Psychological Inflexibility and Psychological Distress.

Int J Ment Health Addict 2021 Aug 26:1-17. Epub 2021 Aug 26.

Faculty of Medicine and Health Science, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.

The COVID-19 pandemic has resulted in multiple physical and psychological stressors, which require quantification and establishment of association with other psychological process variables. The Coronavirus Stress Measure (CSM) is a validated instrument with acceptable validity and reliability. This study aimed to examine the psychometric properties of the CSM in a Malaysian population. Read More

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Predicting spatiotemporally-resolved mean air temperature over Sweden from satellite data using an ensemble model.

Environ Res 2021 Aug 28;204(Pt A):111960. Epub 2021 Aug 28.

Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA. Electronic address:

Mapping of air temperature (Ta) at high spatiotemporal resolution is critical to reducing exposure assessment errors in epidemiological studies on the health effects of air temperature. In this study, we applied a three-stage ensemble model to estimate daily mean Ta from satellite-based land surface temperature (Ts) over Sweden during 2001-2019 at a high spatial resolution of 1 × 1 km. The ensemble model incorporated four base models, including a generalized additive model (GAM), a generalized additive mixed model (GAMM), and two machine learning models (random forest [RF] and extreme gradient boosting [XGBoost]), and allowed the weights for each model to vary over space, with the best-performing model for each grid cell assigned the highest weight. Read More

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Design and Implementation of a Wireless Medical Robot for Communication Within Hazardous Environments.

Wirel Pers Commun 2021 Aug 26:1-22. Epub 2021 Aug 26.

Faculty of Medicine, Ain Shams University, Cairo, Egypt.

The huge spreading of COVID-19 viral outbreak to several countries motivates many of the research institutions everywhere in numerous disciplines to try decreasing the spread rate of this pandemic. Among these researches are the robotics with different payloads and sensory devices with wireless communications to remotely track patients' diagnosis and their treatment. That is, it reduces direct contact between the patients and the medical team members. Read More

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Tracking droplets in soft granular flows with deep learning techniques.

Eur Phys J Plus 2021 21;136(8):864. Epub 2021 Aug 21.

Center for Life Nano- & Neuro-Science, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy.

The state-of-the-art deep learning-based object recognition YOLO algorithm and object tracking DeepSORT algorithm are combined to analyze digital images from fluid dynamic simulations of multi-core emulsions and soft flowing crystals and to track moving droplets within these complex flows. The YOLO network was trained to recognize the droplets with synthetically prepared data, thereby bypassing the labor-intensive data acquisition process. In both applications, the trained YOLO + DeepSORT procedure performs with high accuracy on the real data from the fluid simulations, with low error levels in the inferred trajectories of the droplets and independently computed ground truth. Read More

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Prediction of the COVID-19 infectivity and the sustainable impact on public health under deep learning algorithm.

Soft comput 2021 Aug 21:1-10. Epub 2021 Aug 21.

The Third Clinical Medical College of China Three Gorges University, Gezhouba Central Hospital of Sinopharm, Yichang, 443002 China.

The aim is to explore the development trend of COVID-19 (Corona Virus Disease 2019) and predict the infectivity of 2019-nCoV (2019 Novel Coronavirus), as well as its impact on public health. First, the existing data are analyzed through data pre-processing to extract useful feature factors. Then, the LSTM (Long-Short Term Memory) prediction model in the deep learning algorithm is used to predict the epidemic situation in Hubei Province, outside Hubei nationwide, and the whole country, respectively. Read More

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Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants.

Sensors (Basel) 2021 Aug 22;21(16). Epub 2021 Aug 22.

School of Engineering, University of Portsmouth, Winston Churchill Ave., Portsmouth PO1 3HJ, UK.

Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. Read More

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Investigation of sag behaviour for aluminium conductor steel reinforced considering tensile stress distribution.

R Soc Open Sci 2021 Aug 11;8(8):210049. Epub 2021 Aug 11.

School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, People's Republic of China.

Sag calculation plays an important role in overhead line design. Since the tensile stress of aluminium conductor steel reinforced (ACSR) is required for the sag calculation, an analysis on sag behaviour when considering the tensile stress distribution can be very useful to improve the accuracy of sag results. First, this paper analyses the ACSR tensile stress distribution arising from the temperature maldistribution through proposing a new calculation formula. Read More

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Internet of Things Applications: Opportunities and Threats.

Wirel Pers Commun 2021 Aug 18:1-26. Epub 2021 Aug 18.

Department of Computer Science, Khazar University, Baku, Azerbaijan.

In the century of automation, which is digitized, and more and more technology is used, automatic systems' replacement of old manual systems makes people's lives easier. Nowadays, people have made the Internet an integral part of humans' daily lives unless they are insecure. The Internet of Things (IoT) secures a platform that authorizes devices and sensors to be remotely detected, connected, and controlled over the Internet. Read More

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Reconnecting in the Face of Exclusion: Individuals with High Social Anxiety May Feel the Push of Social Pain, but not the Pull of Social Rewards.

Cognit Ther Res 2021 Aug 17:1-16. Epub 2021 Aug 17.

Department of Psychology and Centre for Mental Health Research and Treatment, University of Waterloo, Waterloo, ON N2L-3G1 Canada.

Background: Previous research has shown that high levels of trait social anxiety (SA) disrupt the social repair processes following a painful social exclusion, but the cognitive mechanisms involved in these processes and how trait SA may disrupt them remain unknown.

Methods: We conducted a preregistered study on Prolific participants ( = 452) who were assigned to experience either social exclusion or inclusion and were then exposed to follow-up opportunities for social reconnection.

Results: Moderated mediation analyses revealed that irrespective of levels of SA, participants responded to social pain with heightened approach motivation and greater downstream positive affect. Read More

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Predicting special care during the COVID-19 pandemic: a machine learning approach.

Health Inf Sci Syst 2021 Dec 14;9(1):34. Epub 2021 Aug 14.

Faculdade de Ciências Aplicadas - Universidade Estadual de Campinas, Limeira, Brazil.

More than ever, COVID-19 is putting pressure on health systems worldwide, especially in Brazil. In this study, we propose a method based on statistics and machine learning that uses blood lab exam data from patients to predict whether patients will require special care (hospitalization in regular or special-care units). We also predict the number of days the patients will stay under such care. Read More

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December 2021

Evaluation of a novel mobile phone application for blood pressure monitoring: a proof of concept study.

J Clin Monit Comput 2021 Aug 18. Epub 2021 Aug 18.

Department of Anesthesiology, Erasme Hospital, Université Libre de Bruxelles, 808 route de lennik, 1070, Brussels, Belgium.

To provide information about the clinical relevance of blood pressure (BP) measurement differences between a new smartphone application (OptiBP™) and the reference method (automated oscillometric technique) using a noninvasive brachial cuff in patients admitted to the emergency department. We simultaneously recorded three BP measurements using both the reference method and the novel OptiBP™ (test method), except when the inter-arm difference was > 10 mmHg BP. Each OptiBP™ measurement required 1-min and the subsequent reference method values were compared to the values obtained with OptiBP™ using a Bland-Altman analysis and error grid analysis. Read More

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Does the Addition of Serum PAPP-A and -hCG Improve the Predictive Value of Uterine Artery Pulsatility Index for Preeclampsia at 11-14 Weeks of Gestation? A Prospective Observational Study.

J Obstet Gynaecol India 2021 Jun 21;71(3):226-234. Epub 2021 Jan 21.

Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.

Purpose Of Study: To study the role of uterine artery Doppler pulsatility index (UtA-PI), serum pregnancy-associated plasma protein-A (PAPP-A) and free beta human chorionic gonadotropin (f-hCG) levels, individually and in combination with each other, at 11-14 weeks of gestation for prediction of preeclampsia (PE).

Methods: In a prospective observational study, a total of 100 low-risk gravid females were recruited at 11-14-weeks of gestation. UtA-PI, PAPP-A and f-hCG levels were estimated. Read More

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Identification of the ARX Model with Random Impulse Noise Based on Forgetting Factor Multi-error Information Entropy.

Shaoxue Jing

Circuits Syst Signal Process 2021 Aug 12:1-18. Epub 2021 Aug 12.

School of Physics and Electronic Electrical Engineering, Huaiyin Normal University, Huaian, 223300 Jiangsu China.

Entropy has been widely applied in system identification in the last decade. In this paper, a novel stochastic gradient algorithm based on minimum Shannon entropy is proposed. Though needing less computation than the mean square error algorithm, the traditional stochastic gradient algorithm converges relatively slowly. Read More

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